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20 pages, 1722 KiB  
Article
Attempted Transmission of Marburg Virus by Bat-Associated Fleas Thaumapsylla breviceps breviceps (Ischnopsyllidae: Thaumapsyllinae) to the Egyptian Rousette Bat (Rousettus aegyptiacus)
by Janusz T. Pawęska, Nadia Storm, Petrus Jansen van Vuren, Wanda Markotter and Alan Kemp
Viruses 2024, 16(8), 1197; https://doi.org/10.3390/v16081197 - 25 Jul 2024
Viewed by 745
Abstract
Egyptian rousette bats (ERBs) are implicated as reservoir hosts for Marburg virus (MARV), but natural mechanisms involved in maintenance of MARV in ERB populations remain undefined. A number of hematophagous ectoparasites, including fleas, parasitize bats. Subcutaneous (SC) inoculation of ERBs with MARV consistently [...] Read more.
Egyptian rousette bats (ERBs) are implicated as reservoir hosts for Marburg virus (MARV), but natural mechanisms involved in maintenance of MARV in ERB populations remain undefined. A number of hematophagous ectoparasites, including fleas, parasitize bats. Subcutaneous (SC) inoculation of ERBs with MARV consistently results in viremia, suggesting that infectious MARV could be ingested by blood-sucking ectoparasites during feeding. In our study, MARV RNA was detected in fleas that took a blood meal during feeding on viremic bats on days 3, 7, and 11 after SC inoculation. Virus concentration in individual ectoparasites was consistent with detectable levels of viremia in the blood of infected host bats. There was neither seroconversion nor viremia in control bats kept in close contact with MARV-infected bats infested with fleas for up to 40 days post-exposure. In fleas inoculated intracoelomically, MARV was detected up to 14 days after intracoelomic (IC) inoculation, but the virus concentration was lower than that delivered in the inoculum. All bats that had been infested with inoculated, viremic fleas remained virologically and serologically negative up to 38 days after infestation. Of 493 fleas collected from a wild ERB colony in Matlapitsi Cave, South Africa, where the enzootic transmission of MARV occurs, all tested negative for MARV RNA. While our findings seem to demonstrate that bat fleas lack vectorial capacity to transmit MARV biologically, their role in mechanical transmission should not be discounted. Regular blood-feeds, intra- and interhost mobility, direct feeding on blood vessels resulting in venous damage, and roosting behaviour of ERBs provide a potential physical bridge for MARV dissemination in densely populated cave-dwelling bats by fleas. The virus transfer might take place through inoculation of skin, mucosal membranes, and wounds when contaminated fleas are squashed during auto- and allogrooming, eating, biting, or fighting. Full article
(This article belongs to the Special Issue Zoonotic and Vector-Borne Viral Diseases)
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<p>Experiment I. Number, sex of bats, MARV inoculation status, and the number of bat fleas released on Egyptian rousette bats. B = bat identification number 1–12; green outline = female; blue outline = male; number on the bat = number of fleas released on each bat; coloured-in bats = bats inoculated with Marburg virus; uncoloured bats = mock-inoculated bats.</p>
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<p>Experiment II. Number, sex of bats, and the number of MARV-inoculated fleas released on Egyptian rousette bats. B = bat identification number 13–29; green outline = female; blue outline = male; number on the bat = number of MARV-inoculated flies released on each bat.</p>
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<p>Female (<b>A</b>) and male (<b>B</b>) bat fleas <span class="html-italic">Thaumapsylla breviceps breviceps</span> collected from <span class="html-italic">Rousettus aegyptiacus</span> bats at Matlapitsi Cave, Matlapitsi Valley, Limpopo Province, South Africa.</p>
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14 pages, 1531 KiB  
Article
An Effective Biochar Application for Reducing Nitrogen Emissions from Buffalo Digestate Storage Tank
by Ester Scotto di Perta, Paola Giudicianni, Antonio Mautone, Corinna Maria Grottola, Elena Cervelli, Raffaele Ragucci and Stefania Pindozzi
Appl. Sci. 2024, 14(15), 6456; https://doi.org/10.3390/app14156456 - 24 Jul 2024
Viewed by 486
Abstract
Open manure storage contributes to the release of ammonia (NH3) into the atmosphere. Tank floating covers represent an effective technique to reduce NH3 emissions and biochar has been gain attention as a floating cover and as manure additive. Nevertheless, the [...] Read more.
Open manure storage contributes to the release of ammonia (NH3) into the atmosphere. Tank floating covers represent an effective technique to reduce NH3 emissions and biochar has been gain attention as a floating cover and as manure additive. Nevertheless, the mechanisms involved in the process still need to be elucidated since they are influenced by the biochar specific properties, application methods and dose. This work aims to study: (i) the biochar adsorption performances in an NH3 aqueous solution under conditions relevant to manure storage and (ii) the effect of different biochar application methods and dosage on NH3 emissions from buffalo digestate storage. The results show that a 43% reduction in NH3 emissions can be achieved by using biochar as a floating cover of 2 cm rather than as an additive. Moreover, the results show that the biochar produced at 550 °C acts as an adsorbent material for both NH4+ and NH3, by being adsorbed on the biochar surface in the form of NH4+ after H+ abstraction from the acid groups. A minimum cover height of 2 cm is required to give compactness and provide an additional resistance to the gas transfer, which is even more relevant than the adsorption in reducing NH3 emissions. Full article
(This article belongs to the Section Agricultural Science and Technology)
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<p>(<b>a</b>) Biochar mixed with the liquid solution (M) and (<b>b</b>) a biochar layer placed as a suspended cover on the liquid surface (B<sub>c</sub>).</p>
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<p>NH<sub>3</sub> emission rates and pH as function of time for 2B (2 cm biochar layer), 1B (1 cm biochar layer) and Bm (biochar mixed with digestate).</p>
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<p>(<b>a</b>) The 1B cover breaking and sinking after 21 days; (<b>b</b>) Biochar floating and forming a crust after 3 weeks; (<b>c</b>) Volume reduction consequent to water evaporation after 50 days.</p>
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<p>Biochar equilibrium adsorption capacity of NH<sub>4</sub><sup>+</sup> (Q<sub>e</sub>) at increasing concentrations of N-NH<sub>4</sub><sup>+</sup> (C<sub>0</sub>) (T = 25 °C).</p>
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23 pages, 2561 KiB  
Review
Non-Ebola Filoviruses: Potential Threats to Global Health Security
by Yannick Munyeku-Bazitama, Francois Edidi-Atani and Ayato Takada
Viruses 2024, 16(8), 1179; https://doi.org/10.3390/v16081179 - 23 Jul 2024
Viewed by 1257
Abstract
Filoviruses are negative-sense single-stranded RNA viruses often associated with severe and highly lethal hemorrhagic fever in humans and nonhuman primates, with case fatality rates as high as 90%. Of the known filoviruses, Ebola virus (EBOV), the prototype of the genus Orthoebolavirus, has [...] Read more.
Filoviruses are negative-sense single-stranded RNA viruses often associated with severe and highly lethal hemorrhagic fever in humans and nonhuman primates, with case fatality rates as high as 90%. Of the known filoviruses, Ebola virus (EBOV), the prototype of the genus Orthoebolavirus, has been a major public health concern as it frequently causes outbreaks and was associated with an unprecedented outbreak in several Western African countries in 2013–2016, affecting 28,610 people, 11,308 of whom died. Thereafter, filovirus research mostly focused on EBOV, paying less attention to other equally deadly orthoebolaviruses (Sudan, Bundibugyo, and Taï Forest viruses) and orthomarburgviruses (Marburg and Ravn viruses). Some of these filoviruses have emerged in nonendemic areas, as exemplified by four Marburg disease outbreaks recorded in Guinea, Ghana, Tanzania, and Equatorial Guinea between 2021 and 2023. Similarly, the Sudan virus has reemerged in Uganda 10 years after the last recorded outbreak. Moreover, several novel bat-derived filoviruses have been discovered in the last 15 years (Lloviu virus, Bombali virus, Měnglà virus, and Dehong virus), most of which are poorly characterized but may display a wide host range. These novel viruses have the potential to cause outbreaks in humans. Several gaps are yet to be addressed regarding known and emerging filoviruses. These gaps include the virus ecology and pathogenicity, mechanisms of zoonotic transmission, host range and susceptibility, and the development of specific medical countermeasures. In this review, we summarize the current knowledge on non-Ebola filoviruses (Bombali virus, Bundibugyo virus, Reston virus, Sudan virus, Tai Forest virus, Marburg virus, Ravn virus, Lloviu virus, Měnglà virus, and Dehong virus) and suggest some strategies to accelerate specific countermeasure development. Full article
(This article belongs to the Section Animal Viruses)
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<p>Locations of bat-derived filovirus detection. Countries in which bat-derived filoviruses have been detected by virus isolation or metagenomic analyses are shown in light green, with exact locations indicated by dots.</p>
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<p>Locations of Ebola and Marburg disease outbreaks and primary cases caused by non-Ebola filoviruses in humans, NHPs, and pigs. Countries in which non-Ebola filovirus human or NHP outbreaks/primary cases, or swine cases were reported are shown in light blue. Countries in which MARV was detected in fruit bats but no human case has been reported are shown in pastel orange. Exact locations are indicated by dots. Outbreaks due to laboratory exposure (Russia) and historically reported outbreak epicenters in Germany and Serbia (ex-Yugoslavia) are depicted. Imported MARV cases in the United States and the Netherlands are also represented.</p>
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17 pages, 1218 KiB  
Article
Smartphone-Based Task Scheduling in UAV Networks for Disaster Relief
by Lin Li, Zhenchuan Wang, Jinqi Zhu and Shizhao Ma
Electronics 2024, 13(15), 2903; https://doi.org/10.3390/electronics13152903 - 23 Jul 2024
Viewed by 445
Abstract
Earthquake disasters are usually very destructive and pose a great threat to human life and property. Based on the relatively mature technology of unmanned aerial vehicles (UAVs) and their high flexibility, these devices are widely used for information collection and processing in post-disaster [...] Read more.
Earthquake disasters are usually very destructive and pose a great threat to human life and property. Based on the relatively mature technology of unmanned aerial vehicles (UAVs) and their high flexibility, these devices are widely used for information collection and processing in post-disaster relief operations. However, UAVs are limited by their battery capacity, which makes it hard for them to perform both large-scale information gathering and data processing at the same time. Nowadays, smartphones (SPs), which have become portable devices for people, have the characteristics of strong computing power, rich communication means and wide distribution. Therefore, in this study, we developed SPs to assist UAVs in computation incentive-based task execution. To balance the cost of UAVs and the execution utility of SPs during the task execution process, a multi-objective optimization problem was established, and the Multi-Objective Mutation-Immune Bat (MOMIB) algorithm was developed to optimize the proposed problem. Additionally, considering the diversity of tasks in real-world scenarios, Quality of Service (QoS) coefficients were introduced to ensure the performance requirements of different types of tasks. A large number of simulation experiments show that the task-offloading scheme that we propose is effective. Full article
(This article belongs to the Section Computer Science & Engineering)
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<p>System model.</p>
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<p>Performance comparison between different baseline approaches and MOMIB. (<b>a</b>) System overhead of UAVs. (<b>b</b>) Execution utility of SPs.</p>
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<p>Variation in system performance with number of tasks in mild disaster scenario. (<b>a</b>) Variation in total UAV overhead with number of tasks. (<b>b</b>) Variation in total utility of SPs with number of tasks.</p>
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<p>Variation in system performance with number of SPs in mild disaster scenario. (<b>a</b>) Variation in total UAV overhead with number of SPs. (<b>b</b>) Variation in total SPs utility with number of SPs.</p>
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<p>Variation in each objective with MOMIB iterations. (<b>a</b>) System overhead of UAVs. (<b>b</b>) Execution utility of SPs.</p>
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<p>Performance of MOMIB in TE. (<b>a</b>) Variation in system overhead of UAVs in TE. (<b>b</b>) Variation in execution utility of SPs in TE.</p>
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13 pages, 4766 KiB  
Article
Identification and Characterization of an Alphacoronavirus in Rhinolophus sinicus and a Betacoronavirus in Apodemus ilex in Yunnan, China
by Qian Liu, Dan-Shu Wang, Zhong-Hao Lian, Jie Fang, Pei-Yu Han, Ye Qiu, Jun-Ying Zhao, Li-Dong Zong, Yun-Zhi Zhang and Xing-Yi Ge
Microorganisms 2024, 12(7), 1490; https://doi.org/10.3390/microorganisms12071490 - 21 Jul 2024
Viewed by 725
Abstract
Coronaviruses (CoVs), the largest positive-sense RNA viruses, have caused infections in both humans and animals. The cross-species transmission of CoVs poses a serious threat to public health. Rodents and bats, the two largest orders of mammals, serve as significant natural reservoirs for CoVs. [...] Read more.
Coronaviruses (CoVs), the largest positive-sense RNA viruses, have caused infections in both humans and animals. The cross-species transmission of CoVs poses a serious threat to public health. Rodents and bats, the two largest orders of mammals, serve as significant natural reservoirs for CoVs. It is important to monitor the CoVs carried by bats and rodents. In this study, we collected 410 fecal samples from bats and 74 intestinal samples from rats in Yunnan Province, China. Using RT-PCR, we identified one positive sample for alphacoronavirus (TC-14) from Rhinolophus sinicus (Chinese rufous horseshoe bat) and two positive samples for betacoronavirus (GS-53, GS-56) from Apodemus ilex (Rodentia: Muridae). We successfully characterized the complete genomes of TC-14 and GS-56. Phylogenetic analysis revealed that TC-14 clustered with bat CoV HKU2 and SADS-CoV, while GS-56 was closely related to rat CoV HKU24. The identification of positive selection sites and estimation of divergence dates further helped characterize the genetic evolution of TC-14 and GS-56. In summary, this research reveals the genetic evolution characteristics of TC-14 and GS-56, providing valuable references for the study of CoVs carried by bats and rodents in Yunnan Province. Full article
(This article belongs to the Special Issue Pathogen Infection in Wildlife 2.0)
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<p>The maximum likelihood tree of RNA-dependent RNA polymerase (RdRp) sequences of TC-14, GS-56, and other CoVs. The tree was constructed using IQ-tree with LG + F + I + G4 substitution model and 10,000 ultrafast bootstraps. The scale bar indicates amino acid substitution per site, and four genera of coronavirus are marked on the side. The TC-14 and GS-56 are marked in red and with a triangle.</p>
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<p>Phylogenetic trees of amino acid sequences of S and N proteins of TC-14 and GS-56 CoVs. These trees were constructed using IQ-tree with 10,000 ultrafast bootstraps, and their substitution models are as follows: WAG + F + I + G4, pfam + F + I + G4, WAG + F + G4, pfam + F + G4, respectively. The accession number, taxonomy, and host of each sequence are displayed. TC-14 and GS-56 are marked in red and with a triangle.</p>
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<p>Multiple alignments of S1 region of TC-14, SADS-CoV, and SADSr-CoV. The accession number and host of the selective sequences are shown. The annotation of the NTD domain in S1 is with reference to SADS-CoV; the NTD domain is marked with a blue line, and the CTD domain is marked with a green line. The short horizontal line indicated the identical sites. * indicates odd multiples of ten of the amino acid.</p>
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<p>Multiple alignment of S1 region of GS-56, ChRCoV-HKU24, and RtAp-CoV. The accession number and host of the genomes are shown. The annotation of NTD and CTD domains in S1 is a reference to ChRCoV HKU24. The NTD domain is marked with a blue line, and the CTD domain is marked with a green line. The short horizontal line indicates the identical sites. * indicates odd multiples of ten of the amino acid.</p>
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<p>Maximum clade credibility (MCC) tree with divergence time based on <span class="html-italic">RdRp</span> nucleotide sequence. The substitution model was GTR + F + F + I + G4, the tree was obtained by Model Finder under the BIC standard [<a href="#B37-microorganisms-12-01490" class="html-bibr">37</a>]. The value near the node indicates the age of the node, and the label on the branch represents the Bayesian posterior probability. The arrows are used to accurately locate points of divergence. The species and sampling time of the selected sequences are labeled. The TC-14 and GS-56 are marked in red.</p>
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23 pages, 1839 KiB  
Review
Genetic Diversity of Trypanosoma cruzi in the United States of America: The Least Endemic Country for Chagas Disease
by Arnau Llovera, Alba Abras, Anna Fernández-Arévalo, Cristina Ballart, Sandra Heras, Carmen Muñoz and Montserrat Gállego
Life 2024, 14(7), 901; https://doi.org/10.3390/life14070901 - 19 Jul 2024
Viewed by 836
Abstract
Chagas disease (CD), caused by Trypanosoma cruzi and endemic in Latin America, has become an emergent health problem in non-endemic countries due to human migration. The United States (US) is the non-Latin American country with the highest CD burden and cannot be considered [...] Read more.
Chagas disease (CD), caused by Trypanosoma cruzi and endemic in Latin America, has become an emergent health problem in non-endemic countries due to human migration. The United States (US) is the non-Latin American country with the highest CD burden and cannot be considered as non-endemic, since triatomine vectors and reservoir animals have been found. Populations of T. cruzi are divided into genetic subdivisions, which are known as discrete typing units (DTUs): TcI to TcVI and TcBat. Autochthonous human T. cruzi infection in the US is sporadic, but it may change due to environmental factors affecting the geographic distribution of triatomines. We aimed to perform a literature review of the genetic diversity of T. cruzi in triatomine vectors and mammalian hosts, including human cases, in the US. The 34 analyzed studies revealed the presence of T. cruzi in 18 states, which was mainly concentrated in Texas, Louisiana and New Mexico. TcI and TcIV were the principal DTUs identified, being TcI the most genotyped (42.4%; 917/2164). This study represents a first attempt to compile the molecular epidemiology of T. cruzi in the US, which is fundamental for predicting the progression of the infection in the country and could be of great help in its future management. Full article
(This article belongs to the Section Epidemiology)
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<p>States of US with <span class="html-italic">T. cruzi</span> DTUs genotyped in mammalian hosts (blue), triatomine vectors (yellow) or both (green). In the case of the state of Missouri (MO), Curtis-Robles et al. [<a href="#B75-life-14-00901" class="html-bibr">75</a>] reported a triatomine (<span class="html-italic">Triatoma sanguisuga</span>) resulted positive by PCR for <span class="html-italic">T. cruzi</span> DNA, but it was not possible to type the DTU. The outline map was taken from <a href="https://simplemaps.com/resources/svg-maps" target="_blank">https://simplemaps.com/resources/svg-maps</a>, accessed on 20 June 2024. AL, Alabama; AK, Alaska; AZ, Arizona; AR, Arkansas; CA, California; CO, Colorado; CT, Connecticut; DE, Delaware; FL, Florida; GA, Georgia; HI, Hawaii; ID, Idaho; IL, Illinois; IN, Indiana; IA, Iowa; KS, Kansas; KY, Kentucky; LA, Louisiana; ME, Maine; MD, Maryland; MA, Massachusetts; MI, Michigan; MN, Minnesota; MS, Mississippi; MO, Missouri; MT, Montana; NE, Nebraska; NV, Nevada; NH, New Hampshire; NJ, New Jersey; NM, New Mexico; NY, New York; NC, North Carolina; ND, North Dakota; OH, Ohio; OK, Oklahoma; OR, Oregon; PA, Pennsylvania; RI, Rhode Island; SC, South Carolina; SD, South Dakota; TN, Tennessee; TX, Texas; UT, Utah; VT, Vermont; VA, Virginia; WA, Washington; WI, Wisconsin; WY, Wyoming.</p>
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<p>Trypanosoma cruzi DTUs identification according to the states of the US. (<b>a</b>) Number of cases positive for <span class="html-italic">T. cruzi</span> in mammalian hosts (including humans) and triatomine vectors (n hosts = 815; n vectors = 1349; global n = 2164). States with up to 10 <span class="html-italic">T. cruzi</span> positive cases are shown with an adapted scale in the box at the top of the figure. (<b>b</b>) Percentage of samples typed according to the states of the US. The number of types per state is bracketed. Other mixed infections include TcI + TcII, TcI + TcVI, TcI + TcII + TcVI, TcI + TcII/V, TcI + TcII/V/VI, TcI + TcIV + TcII/V, TcI + TcII + TcV + TcVI, TcI + TcII + TcIV + TcV + TcVI, TcII + TcIV and TcII + TcVI; Unclear DTU, it was not possible to genotype at the level of a single DTU. AL, Alabama; AZ, Arizona; CA, California; FL, Florida; GA, Georgia; IL, Illinois; IN, Indiana; KS, Kansas; KY, Kentucky; LA, Louisiana; MD, Maryland; MO, Missouri; NM, New Mexico; OK, Oklahoma; SC, South Carolina; TN, Tennessee; TX, Texas; VA, Virginia; n.d., state of origin not determined.</p>
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<p><span class="html-italic">Trypanosoma cruzi</span> DTUs identification in mammalian hosts. (<b>a</b>) Number of cases positive for <span class="html-italic">T. cruzi</span> according to the mammal host order (n = 815). (<b>b</b>) Percentage of samples typed according to the mammal host order. The number of types per order are bracketed. The distribution of species within each order is as follows: Chiroptera: evening bat (<span class="html-italic">Nycticeius humeralis</span>) (1); Cingulata: nine-band armadillo (<span class="html-italic">Dasypus novemcinctus</span>) (3); Didelphimorphia: Virginia opossum (<span class="html-italic">Didelphis virginiana</span>) (92); Rodentia: southern plains woodrat (<span class="html-italic">Neotoma micropus</span>) (36), hispid cotton rat (<span class="html-italic">Sigmodon hispidus</span>) (3), rock squirrel (<span class="html-italic">Otospermophilus variegatus</span>) (1), house mouse/cotton mouse (<span class="html-italic">Mus musculus</span> and <span class="html-italic">Peromyscus gossypinus</span>) (34), eastern woodrat (<span class="html-italic">Neotoma floridana</span>) (12), northern pygmy mouse (<span class="html-italic">Bayomis taylori</span>) (1), white-footed mouse (<span class="html-italic">Peromyscus leucopus</span>) (3), hispid pocket mouse (<span class="html-italic">Chaetodipus hispidus</span>) (1), Mexican spiny pocket mouse (<span class="html-italic">Liomys irroratus</span>) (1), house mouse (<span class="html-italic">Mus musculus</span>) (2), cotton mouse (<span class="html-italic">Peromyscus gossypinus</span>) (3), cactus mouse (<span class="html-italic">Peromyscus eremicus</span>) (1); spotted ground squirrel (<span class="html-italic">Xerospermophilus spilosoma</span>) (1), western harvest mouse (<span class="html-italic">Reithrodontomys megalotis</span>) (1); Primate non-human: ring-tailed lemur (<span class="html-italic">Lemur catta</span>) (3), rhesus macaque (<span class="html-italic">Macaca mulatta</span>) (42), pig-tailed macaque (<span class="html-italic">Macaca nemestrina</span>) (2), cynomolgus macaque (<span class="html-italic">Macaca fascicularis</span>) (59), and baboon (<span class="html-italic">Papio</span> spp.) (2); Carnivora: domestic dog (<span class="html-italic">Canis lupus familiaris</span>) (206), raccoon (<span class="html-italic">Procyon lotor</span>) (189), domestic cat (<span class="html-italic">Felis catus</span>) (80), coyote (<span class="html-italic">Canis latrans</span>) (11), striped skunk (<span class="html-italic">Mephitis mephitis</span>) (7), and gray fox (<span class="html-italic">Urocyon cinereoargenteus</span>) (1).</p>
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<p><span class="html-italic">Trypanosoma cruzi</span> DTUs identification in triatomine vectors. (<b>a</b>) Number of cases positive for <span class="html-italic">T. cruzi</span> according to the triatomine species (n = 1349). (<b>b</b>) Percentage of samples typed according to the triatomine species. The number of types per species are bracketed.</p>
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14 pages, 4017 KiB  
Article
Transcriptional Regulation of the Genes Encoding Branched-Chain Aminotransferases in Kluyveromyces lactis and Lachancea kluyveri Is Independent of Chromatin Remodeling
by James González, Héctor Quezada, Jose Carlos Campero-Basaldua, Édgar Ramirez-González, Lina Riego-Ruiz and Alicia González
Microbiol. Res. 2024, 15(3), 1225-1238; https://doi.org/10.3390/microbiolres15030082 - 19 Jul 2024
Viewed by 460
Abstract
In yeasts, the Leu3 transcriptional factor regulates the expression of genes encoding enzymes of the leucine biosynthetic pathway, in which the first committed step is catalyzed by α-isopropylmalate synthase (α-IPMS). This enzyme is feedback inhibited by leucine, and its product, α-isopropylmalate (α-IPM), constitutes [...] Read more.
In yeasts, the Leu3 transcriptional factor regulates the expression of genes encoding enzymes of the leucine biosynthetic pathway, in which the first committed step is catalyzed by α-isopropylmalate synthase (α-IPMS). This enzyme is feedback inhibited by leucine, and its product, α-isopropylmalate (α-IPM), constitutes a Leu3 co-activator. In S. cerevisiae, the ScBAT1 and ScBAT2 genes encode branched-chain aminotransferase isozymes. ScBAT1 transcriptional activation is dependent on the α-IPM concentration and independent of chromatin organization, while that of ScBAT2 is α-IPM-independent but dependent on chromatin organization. This study aimed at understanding whether chromatin remodeling determines the transcriptional regulation of orthologous KlBAT1 and LkBAT1 genes in Kluyveromyces lactis and Lachancea kluyveri under conditions in which the branched-chain amino acids are synthesized or degraded. The results indicate that, in K. lactis, KlBAT1 expression is reduced under catabolic conditions, while in L. kluyveri, LkBAT1 displays a constitutive expression profile. The chromatin organization of KlBAT1 and LkBAT1 promoters did not change, maintaining the Leu3-binding sites free of nucleosomes. Comparison of the α-IPMS sensitivities to feedback inhibition suggested that the main determinant of transcriptional activation of the KlBAT1 and LkBAT1 genes might be the availability of the α-IPM co-activator, as reported previously for the ScBAT1 gene of S. cerevisiae. Full article
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<p>Schematic representation of the leucine synthesis pathway in <span class="html-italic">S. cerevisiae</span> (<b>a</b>) and the evolutionary history of genes encoding BCATs (<b>b</b>). (<b>a</b>) The mitochondrial part of the pathway is conformed by acetolactate synthases (Ilv2/Ilv6), acetohydroxi acid reductoisomerase (Ilv5), dihydroxi acid dehydratase (Ilv3), leucine-sensitive α-isopropylmalate synthase (Leu4), leucine-resistant α-isopropylmalate synthase (Leu9), and branched-chain aminotransferase (Bat1). The cytosolic part of the pathway is conformed by isopropyl malate isomerase (Leu1), α-IPM dehydrogenase (Leu2), and branched-chain aminotransferase (Bat2). Pathway intermediates are pyruvate (PYR), acetolactate (AL), α,β-dehydroxyisovalerate (DHIV), α-ketoisovalerate (KIV), α-isopropylmalate (α-IPM), β-isopropylmalate (β-IPM), α-ketoisocaproate (KIC), and leucine. The dotted line represents a negative allosteric feedback loop. High levels of α-IPM trigger the active form of Leu3 (Leu3-α-IPM) into the nucleus to promote transcription of the genes <span class="html-italic">LEU4</span>, <span class="html-italic">ILV2</span>, <span class="html-italic">ILV5, LEU1</span>, <span class="html-italic">LEU2</span>, <span class="html-italic">BAT1</span>, and <span class="html-italic">GDH1</span>. The enzymes Ilv2, Ilv5, Ilv3, Bat1, and Bat2 also participate in the synthesis of valine and isoleucine; for clarity, the corresponding reactions are not shown. (<b>b</b>) Phylogenetic tree, extracted from PhylomeDB (<a href="http://phylomedb.org/" target="_blank">http://phylomedb.org/</a> accessed on 9 February 2024), comprising the orthologs of the <span class="html-italic">S. cerevisiae</span> Bat1 (marked with a red box) and Bat2 (marked with a green sphere) proteins; duplication events are shown as red squares and speciation events as blue squares.</p>
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<p>Transcriptional repression of the branched-chain aminotransferase-encoding gene is observed for the <span class="html-italic">KlBAT1</span> gene from <span class="html-italic">K. lactis</span> but not for the <span class="html-italic">LkBAT1</span> from <span class="html-italic">L. kluyveri</span> when VIL is used as nitrogen source. Total RNA was extracted from <span class="html-italic">K. lactis</span> (<b>a</b>), <span class="html-italic">L. kluyveri</span> (<b>b</b>), or <span class="html-italic">S. cerevisiae</span> (<b>c</b>,<b>d</b>) wild-type strains. qPCR analysis was carried out using the corresponding <span class="html-italic">18S</span> genes as constitutive controls and the 2<sup>−ΔΔCT</sup> method to compare the transcript levels in glutamine (Gln, 7 mM) or valine (V, 150 mg L<sup>−1</sup>) + isoleucine (I, 30 mg L<sup>−1</sup>) + leucine (L, 100 mg L<sup>−1</sup>) (VIL) as the sole nitrogen source. Yeast cultures were grown on 2% glucose to an OD<sub>600</sub> = 0.5. For reference, regulation of the <span class="html-italic">ScBAT1</span> and <span class="html-italic">ScBAT2</span> genes from <span class="html-italic">S. cerevisiae</span> is shown, as expected, transcription of the <span class="html-italic">ScBAT1</span> gene is repressed on VIL (<b>c</b>), while that of <span class="html-italic">ScBAT2</span> is induced (<b>d</b>) [<a href="#B8-microbiolres-15-00082" class="html-bibr">8</a>]. Experiments were performed in triplicate and data are presented as mean ± standard error of the mean.</p>
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<p>Chromatin remodeling of the <span class="html-italic">KlBAT1</span> and <span class="html-italic">LkBAT1</span> promoter regions is not dependent on the nitrogen source. NuSA analysis was performed with mono-nucleosomes prepared from the <span class="html-italic">K. lactis</span> (<b>a</b>) or <span class="html-italic">L. kluyveri</span> (<b>b</b>) wild-type strains grown on Gln (lines in dark color) or VIL (a mix of 150 mg L<sup>−1</sup> valine + 30 mg L<sup>−1</sup> isoleucine + 100 mg L<sup>−1</sup> leucine, lines in light color) as the sole nitrogen source, as described in <a href="#sec2-microbiolres-15-00082" class="html-sec">Section 2</a>. NuSA examined nucleosome occupancy at the <span class="html-italic">KlBAT1</span> and <span class="html-italic">LkBAT1</span> loci, including the 5′ −600 bp of the intergenic region and the 3′ +200 bp of the <span class="html-italic">KlBAT1</span> (<b>a</b>) and <span class="html-italic">LkBAT1</span> (<b>b</b>). MNase-treated chromatin and purified DNA samples and mononucleosome-sized (140–160) fragments were prepared, as described in <a href="#sec2-microbiolres-15-00082" class="html-sec">Section 2</a>. The resulting material was analyzed with a set of overlapping primer pairs covering the <span class="html-italic">KlBAT1</span> and <span class="html-italic">LkBAT1</span> loci (<a href="#app1-microbiolres-15-00082" class="html-app">Tables S2 and S3</a>). Relative <span class="html-italic">KlBAT1</span> and <span class="html-italic">LKBAT1</span> MNase protection was calculated as the ratio of template present in MNase digested DNA over the amount of MNase protection observed for the <span class="html-italic">KlVCX1</span> or <span class="html-italic">LKVCX1</span> locus, respectively, which was used as control (<a href="#app1-microbiolres-15-00082" class="html-app">Figure S1</a>). Data are presented as the average of three independent experiments along with the standard error of the mean. The diagram of the <span class="html-italic">KlBAT1</span> or <span class="html-italic">LkBAT1</span> promoter was extrapolated from the MNase protection data and depicts nucleosome positioning. Grey ovals indicate firmly positioned nucleosomes; white ovals with dotted borders depict relative occupancy. Black arrows indicate transcription activation. Black boxes correspond to the Leu3-binding sites and <span class="html-italic">TATA<sub>BOX</sub></span>. NFR—nucleosome-free region. Yeast cultures were grown to an OD<sub>600</sub> = 0.5 on 2% glucose with either glutamine (Gln, 7 mM) or valine (V, 150 mg L<sup>−1</sup>) + isoleucine (I, 30 mg L<sup>−1</sup>) + leucine (L, 100 mg L<sup>−1</sup>) (VIL) as the sole nitrogen source. Experiments were performed in triplicate, and data are presented as mean ± standard deviation. (<b>c</b>,<b>d</b>) Analysis of leucine sensitivity of the α-IPMS enzymes through comparison of the inhibitor concentration necessary to inhibit the activity by 50% at saturating substrate concentrations (IC50) of crude extracts obtained from <span class="html-italic">Klleu4bis</span>Δ and <span class="html-italic">Klleu4</span>Δ (<b>c</b>) and <span class="html-italic">Lkleu4bis</span>Δ and <span class="html-italic">Lkleu4</span>Δ (<b>d</b>) single-mutant strains grown with 2% glucose plus ammonium sulfate 7 mM. Results are averages of at least two biological replicates.</p>
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<p><span class="html-italic">KlBAT1</span> and <span class="html-italic">LkBAT1</span> promoters contain a putative Leu3-binding site in the NFR. In silico promoter analysis was performed as described in <a href="#sec2-microbiolres-15-00082" class="html-sec">Section 2</a>. (<b>a</b>,<b>c</b>) <span class="html-italic">KlBAT1</span> promoter, and (<b>b</b>,<b>d</b>) <span class="html-italic">LkBAT1</span> promoter. In (<b>a</b>,<b>b</b>), transcription factor binding sites are indicated as vertical-colored coded rectangles, as shown in the lower part of the figure. Ovals indicate fixed positioned nucleosomes for each analyzed promoter under Gln or VIL (a mix of 150 mg L<sup>−1</sup> valine + 30 mg L<sup>−1</sup> isoleucine + 100 mg L<sup>−1</sup> leucine) conditions. In (<b>c</b>,<b>d</b>), sequences from 600 bp upstream to +1 ATG of <span class="html-italic">KlBAT1</span> and <span class="html-italic">LkBAT1</span> are shown with transcription factor binding sites that were found using YEASTRACT. For <span class="html-italic">KlBAT1</span>, consensus sites for <span class="html-italic">HAP2</span>, <span class="html-italic">GCN4</span>, <span class="html-italic">GLN3-GAT1</span>, <span class="html-italic">NRG1</span>, and the <span class="html-italic">TATA<sub>BOX</sub></span> are highlighted in black. <span class="html-italic">LEU3</span> (blue letters), <span class="html-italic">PUT3</span> (red letters), and <span class="html-italic">NRG1</span> (highlighted in black) consensus sequences are overlapped. For <span class="html-italic">LkBAT1</span>, consensus sites for <span class="html-italic">MOT3</span>, <span class="html-italic">LEU3</span>, <span class="html-italic">GCN4</span>, <span class="html-italic">HAP2</span>, and the <span class="html-italic">TATA<sub>BOX</sub></span> are marked in black. The black arrow indicates transcriptional orientation and +1 ATG. NFR—nucleosome-free region.</p>
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<p>Some regions of the Leu3 protein are highly conserved in <span class="html-italic">K. lactis</span>, <span class="html-italic">S. cerevisiae</span>, and <span class="html-italic">L. kluyveri</span>. The amino acid sequences of the Leu3 proteins from <span class="html-italic">K. lactis</span> (KLLA0D10593g), <span class="html-italic">S. cerevisiae</span> (YLR451W), and <span class="html-italic">L. kluyveri</span> (SAKL0F15444g) were aligned using the SIM tool (<a href="https://web.expasy.org/sim/" target="_blank">https://web.expasy.org/sim/</a> accessed on 16 February 2024). For the sequence of <span class="html-italic">S. cerevisiae</span>, the residues corresponding to the DNA-binding domain are shaded in green, the α-IPM binding domain in cyan, and the activation domain in grey, as described by Zhou and coworkers [<a href="#B2-microbiolres-15-00082" class="html-bibr">2</a>,<a href="#B3-microbiolres-15-00082" class="html-bibr">3</a>]. The conserved residues that bind the everted CGG half-sites and eight adjacent phosphodiester bonds are shaded in yellow. The conserved six cysteine residues that ligate the two zinc ions are shown in red letters [<a href="#B25-microbiolres-15-00082" class="html-bibr">25</a>]. Asterisks represent conserved residues.</p>
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20 pages, 2672 KiB  
Article
Construction and Characterization of a High-Capacity Replication-Competent Murine Cytomegalovirus Vector for Gene Delivery
by André Riedl, Denisa Bojková, Jiang Tan, Ábris Jeney, Pia-Katharina Larsen, Csaba Jeney, Florian Full, Ulrich Kalinke and Zsolt Ruzsics
Vaccines 2024, 12(7), 791; https://doi.org/10.3390/vaccines12070791 - 18 Jul 2024
Viewed by 926
Abstract
We investigated the basic characteristics of a new murine cytomegalovirus (MCMV) vector platform. Using BAC technology, we engineered replication-competent recombinant MCMVs with deletions of up to 26% of the wild-type genome. To this end, we targeted five gene blocks (m01-m17, m106-m109, m129-m141, m144-m158, [...] Read more.
We investigated the basic characteristics of a new murine cytomegalovirus (MCMV) vector platform. Using BAC technology, we engineered replication-competent recombinant MCMVs with deletions of up to 26% of the wild-type genome. To this end, we targeted five gene blocks (m01-m17, m106-m109, m129-m141, m144-m158, and m159-m170). BACs featuring deletions from 18% to 26% of the wild-type genome exhibited delayed virus reconstitution, while smaller deletions (up to 16%) demonstrated reconstitution kinetics similar to those of the wild type. Utilizing an innovative methodology, we introduced large genomic DNA segments, up to 35 kbp, along with reporter genes into a newly designed vector with a potential cloning capacity of 46 kbp (Q4). Surprisingly, the insertion of diverse foreign DNAs alleviated the delayed plaque formation phenotype of Q4, and these large inserts remained stable through serial in vitro passages. With reporter-gene-expressing recombinant MCMVs, we successfully transduced not only mouse cell lines but also non-rodent mammalian cells, including those of human, monkey, bovine, and bat origin. Remarkably, even non-mammalian cell lines derived from chickens exhibited successful transduction. Full article
(This article belongs to the Special Issue Viral Vector-Based Vaccines and Therapeutics)
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Figure 1

Figure 1
<p>(<b>a</b>) The genomic organization of MCMVs (adapted from [<a href="#B26-vaccines-12-00791" class="html-bibr">26</a>]) features distinct gene blocks. Centrally positioned are the core genes (depicted by black boxes), which exhibit high conservation across herpesvirus families. Adjacent to the core genes are the CMV-specific genes (depicted in light gray and denoted with ‘C’). Towards the termini, homologs shared among the β-herpesviruses are observed (dark gray boxes denoted with ‘β’). Large gene blocks specific to MCMVs are located at the termini (white boxes). To enhance the cargo load capacity, up to five gene blocks of accessory genes (ΔI-V) were selectively deleted. (<b>b</b>) The MCMV vector map illustrates the wild-type MCMV-BAC [<a href="#B47-vaccines-12-00791" class="html-bibr">47</a>] and the BAC cassette (white box, denoted with ‘BAC’) that was inserted between the deletion clusters II and III to create a circular genome intermediate. The Q4 vector (featuring combined deletions ΔI-IV) and the indicated insertion sites for different site-specific recombinases (open triangles denoted with FRT, loxP, and rox) and an insertion mutant (Q4-LRBAs) were designed to restore the genome size nearly to that of the wild type (the stuffer is indicated by the striped box). The Q4 vector provides a cargo load capacity of almost 46 kbp. Q4-LRBAs represent loaded Q4 vectors with an insert of approximately 37 kbp. (<b>c</b>) Depicted is the result of a multistep growth analysis carried out by infecting MEFs with ΔI+II-GLuc and Q4-LRBAs-GLuc in comparison with the BAC-derived MCMV-wt Smith strain at an MOI of 0.1. Supernatants were collected on the indicated days and titrated using a plaque assay in technical triplicate. The viral titers depicted in (c) represent the results of a single representative experiment. (<b>d</b>) Depicted are multistep growth analyses testing various passages, denoted as P1, P3, and P6, for both the empty MCMV vector Q4 and the cargo-loaded vector Q4-LAD using the BAC-derived MCMV-wt control as described in (<b>c</b>).</p>
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<p>Scale representation of four MCMV genomes characterized in detail in this study. Each genome is represented to scale, illustrating the relative sizes and modifications between the wild-type and the engineered variants. For feature explanation, refer to <a href="#vaccines-12-00791-f001" class="html-fig">Figure 1</a>. (<b>a</b>) Wild-type MCMV genome (MCMV-wt), comprising 230,277 base pairs (bp). (<b>b</b>) Q4 vector, a deletion variant of the MCMV genome, reduced to 184,892 bp by the removal of gene blocks ΔI-ΔIV. (<b>c</b>) Q4-LAD vector, derived from the Q4 vector, incorporating a large insertion termed LAD, resulting in a total genome size of 218,714 bp. (<b>d</b>) Q4-LRBAs-GLuc vector, similar to Q4-LAD but containing the LRBAs-GLuc insertion instead, with a total genome size of 221,226 bp.</p>
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<p>Illumina paired-end sequencing was employed to assess the read coverage of MCMV vectors. DNA extracted from cell-free viruses at designated passages on mouse embryonic fibroblasts (MEFs) served as the sequencing sample. Reads were aligned to reference genomes (see <a href="#app1-vaccines-12-00791" class="html-app">Supplementary Table S3</a> for the GenBank accession numbers), and deletions were further analyzed for the frequency of deletion reads. Panel (<b>a</b>) illustrates the read coverage of the MCMV-wt genome across various passages. Panels (<b>b</b>–<b>d</b>) represent the read coverage for the empty Q4 vector, Q4-LRBAs-GLuc, and Q4-LAD, respectively.</p>
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<p>In vitro transduction efficiency of MCMV vectors in cell lines derived from different species. In panels (<b>a</b>–<b>c</b>), the Gaussian luciferase activity in the supernatant of cultures induced by treatment with the indicated MCMV vectors at an MOI of 3 at 1, 2, and 5 days post-infection (dpi), respectively, is depicted. The luciferase activity was measured indirectly during substrate conversion and is presented here in relative light units (RLUs). Among the transduced cells are fibroblasts of murine, human, and chicken origin, as well as epithelial cells of human, primate, bovine, porcine, canine, bat, and chicken origin. “Mock” represents data from equally treated cells despite viral infection. Data were normalized to the values measured 1 h post-infection (hpi). The values shown are the means of three independent experiments measured in technical triplicate, and the error bars indicate standard deviations. As shown in panels (<b>d</b>,<b>e</b>), the viral genome copies were determined by using M45 gene-specific qPCR at different times after infection of the indicated cell lines with the indicated MCMV vectors. The total DNA extracted from infected MEF, ARPE-19, A549, 293A, 911, and Vero E6 cells was assessed at four different time points (14 hpi, 36 hpi, 3 dpi, and 5 dpi). The resulting viral copy numbers were calculated per haploid genome count, which was determined by using the control qPCR to amplify the GAPDH genes of the respective hosts. (<b>d</b>) The data from three independent experiments are shown pooled together for the MCMV vector ΔI+II-GLuc. (<b>e</b>) Same as (<b>d</b>) for Q4-LRBAs-GLuc.</p>
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<p>Release of infectious particles into the supernatant upon infection of various cells with MCMV–wt (<b>a</b>,<b>d</b>) and the MCMV vectors ΔI+II~–GLuc (<b>b</b>,<b>e</b>) and Q4–LRBAs–GLuc (<b>c</b>,<b>f</b>). The indicated cells were infected with the respective viruses at a multiplicity of infection (MOI) of 3 and washed extensively, and the potentially de novo-generated virions were quantified using a standard plaque assay on murine embryonic fibroblasts (MEFs). In the left panels (<b>a</b>–<b>c</b>), cells that produced a detectable titer at 5 dpi or later are shown. In the right panels (<b>d</b>–<b>f</b>), cells that did not produce infectious virions at 5 days post-infection (dpi) or later are depicted. The titers were particularly high in 911 and Vero E6 cells, in addition to the permissive MEFs. The graphs show the results of data from three independent experiments.</p>
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<p>Heatmaps depicting viral mRNA transcription in MEF, A549, ARPE-19, and 911 cells following infection with either Q4-LRBAs-GLuc (Vec) or wild-type MCMV (WT) at early (8 h post-infection (hpi)) and late (31 hpi) time points. The log2 of normalized read counts by counts per million (cpm) is presented as the MCMV transcript level. Each column corresponds to an individual experiment (mock experiments are split into two replicates). The genes coding for Q4-LRBAs-GLuc are presented. The expression of each gene has been scaled. Samples with relatively high expression of an MCMV gene are marked in red, and samples with relatively low expression are marked in yellow and blue. White areas represent genes with no counts.</p>
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16 pages, 1751 KiB  
Review
Adipose Tissue Dysfunction Related to Climate Change and Air Pollution: Understanding the Metabolic Consequences
by Radoslav Stojchevski, Preethi Chandrasekaran, Nikola Hadzi-Petrushev, Mitko Mladenov and Dimiter Avtanski
Int. J. Mol. Sci. 2024, 25(14), 7849; https://doi.org/10.3390/ijms25147849 - 18 Jul 2024
Viewed by 1371
Abstract
Obesity, a global pandemic, poses a major threat to healthcare systems worldwide. Adipose tissue, the energy-storing organ during excessive energy intake, functions as a thermoregulator, interacting with other tissues to regulate systemic metabolism. Specifically, brown adipose tissue (BAT) is positively associated with an [...] Read more.
Obesity, a global pandemic, poses a major threat to healthcare systems worldwide. Adipose tissue, the energy-storing organ during excessive energy intake, functions as a thermoregulator, interacting with other tissues to regulate systemic metabolism. Specifically, brown adipose tissue (BAT) is positively associated with an increased resistance to obesity, due to its thermogenic function in the presence of uncoupled protein 1 (UCP1). Recently, studies on climate change and the influence of environmental pollutants on energy homeostasis and obesity have drawn increasing attention. The reciprocal relationship between increasing adiposity and increasing temperatures results in reduced adaptive thermogenesis, decreased physical activity, and increased carbon footprint production. In addition, the impact of climate change makes obese individuals more prone to developing type 2 diabetes mellitus (T2DM). An impaired response to heat stress, compromised vasodilation, and sweating increase the risk of diabetes-related comorbidities. This comprehensive review provides information about the effects of climate change on obesity and adipose tissue, the risk of T2DM development, and insights into the environmental pollutants causing adipose tissue dysfunction and obesity. The effects of altered dietary patterns on adiposity and adaptation strategies to mitigate the detrimental effects of climate change are also discussed. Full article
(This article belongs to the Special Issue Lipidomics and Lipid Metabolism in Health and Disease)
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Figure 1
<p>Adipose tissue responses to thermal challenges. (<b>a</b>) In BAT, polarized macrophages, due to cold exposure, directly activate beta-adrenergic signaling, thereby increasing heat production. (<b>b</b>) Energy expenditure is triggered by the body’s cooling mechanisms when the temperature exceeds the thermoneutral zone. (<b>c</b>) The elevated thermogenic activity of brown and beige adipocytes due to cold exposure is a result of increased glucose and free fatty acid uptake. (<b>d</b>) The browning of WAT is an important mechanism in which cold exposure triggers an increase in the oxidative metabolic rates of brown and beige adipocytes. This is essential for maintaining core body temperature during prolonged cold exposure. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Addressing global challenges related to obesity and climate. (<b>a</b>) Obesity is triggered by high levels of greenhouse gas emissions due to increased food intake. (<b>b</b>) An important factor contributing to obesity is the increased time spent in the thermoneutral zone and decreased thermogenesis as a consequence. (<b>c</b>) A protein-rich diet is recommended due to it having the highest effect on diet-induced thermogenesis. (<b>d</b>) The increase in the consumption of processed foods is attributed to increased temperatures negatively impacting crop yields and agriculture. (<b>e</b>) Physical inactivity, as a result of extreme temperatures, contributes to weight gain. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Effects of heat exposure and air pollution on insulin resistance and diabetes complications. (<b>a</b>) Exposure to high temperatures increases sweat secretion and peripheral vasodilation. This, in turn, dissipates heat and maintains optimal body temperature. (<b>b</b>) Impairment of insulin signaling stimulates insulin resistance in various tissues due to dehydration caused by heat exposure. (<b>c</b>) Glucose intolerance is a consequence of disruption of thermoregulation by impairment of orthostatic response. (<b>d</b>) Air pollutants, specifically PM2.5, increase risk of glucose intolerance and type 2 DM-associated cardiovascular diseases. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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19 pages, 6813 KiB  
Article
Dietary Pectin from Premna microphylla Turcz Leaves Prevents Obesity by Regulating Gut Microbiota and Lipid Metabolism in Mice Fed High-Fat Diet
by Jiaobei Gao, Mengxue Zhang, Li Zhang, Nan Wang, Yan Zhao, Daoyuan Ren and Xingbin Yang
Foods 2024, 13(14), 2248; https://doi.org/10.3390/foods13142248 - 17 Jul 2024
Viewed by 709
Abstract
The present study was designed to investigate the protective effects of pectin extracted from Premna microphylla Turcz leaves (PTP) against high-fat-diet (HFD)-induced lipid metabolism disorders and gut microbiota dysbiosis in obese mice. PTP was made using the acid extraction method, and it was [...] Read more.
The present study was designed to investigate the protective effects of pectin extracted from Premna microphylla Turcz leaves (PTP) against high-fat-diet (HFD)-induced lipid metabolism disorders and gut microbiota dysbiosis in obese mice. PTP was made using the acid extraction method, and it was found to be an acidic pectin that had relative mole percentages of 32.1%, 29.2%, and 26.2% for galacturonic acid, arabinose, and galactose, respectively. The administration of PTP in C57BL/6J mice inhibited the HFD-induced abnormal weight gain, visceral obesity, and dyslipidemia, and also improved insulin sensitivity, as revealed by the improved insulin tolerance and the decreased glucose levels during an insulin sensitivity test. These effects were linked to increased energy expenditure, as demonstrated by the upregulation of thermogenesis-related protein UCP1 expression in the brown adipose tissue (BAT) of PTP-treated mice. 16S rRNA gene sequencing revealed that PTP dramatically improved the HFD-induced gut dysbiosis by lowering the ratio of Firmicutes to Bacteroidetes and the quantity of potentially harmful bacteria. These findings may provide a theoretical basis for us to understand the functions and usages of PTP in alleviating obesity. Full article
(This article belongs to the Section Nutraceuticals, Functional Foods, and Novel Foods)
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Figure 1
<p>Chemical analysis of pectin from dietary <span class="html-italic">Premna microphylla</span> Turcz leaves (PTP). (<b>A</b>) FT-IR spectra. (<b>B</b>) Scanning electron microscope images at different magnifications. The HPLC chromatograms of PMP (1-pheny-3-methyl-5-pyrazolone) derivatives of eight standard monosaccharides (<b>C</b>) and component monosaccharides released by hydrolyzing PTP as pectin (<b>D</b>). Peaks: (1) mannose, (2) ribose, (3) rhamnose, (4) glucuronic acid, (5) galacturonic acid, (6) glucose, (7) galactose, (8) arabinose.</p>
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<p>Effects of PTP on body weight, water intake, food consumption, and basic parameters for 12 consecutive weeks of high-fat diet (HFD) feeding in mice (<b>A</b>–<b>F</b>). Hepatosomatic index (HI) = liver weight (g)/body weight (g); fat index (FI) = total fat weight (g)/body weight (g); total fat weight (g) = epididymal white adipose tissue (eWAT) weight (g) + inguinal white adipose tissue (iWAT) weight (g) + mesentery adipose tissue (MAT) weight (g). One-way ANOVA followed by Tukey’s multiple comparisons test was performed for all groups. Values are expressed as means ± SD (<span class="html-italic">n</span> = 8). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 and ns indicates no significant difference.</p>
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<p>Effects of PTP on histopathological changes in hepatocytes in the liver and three different adipocytes stained with H&amp;E, and original magnification 200×. The diameters of adipocytes were determined by ImageJ software (version 1.54) (<span class="html-italic">n</span> = 8 per group). (<b>A</b>) Histopathological alterations of the livers and the adipose tissues stained by H&amp;E (original magnification of 400×). (<b>B</b>–<b>D</b>) The diameters of epididymal white adipose tissue (eWAT) and inguinal white adipose tissue (iWAT) as well as brown adipose tissue (BAT), respectively. # <span class="html-italic">p</span> &lt; 0.05 and ### <span class="html-italic">p</span> &lt; 0.001, versus the ND mice. ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001, versus the HFD mice.</p>
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<p>Effects of PTP on lipid metabolism and its related factors, adiponectin (ADPN) and lipopolysaccharide (LPS), in HFD-fed mice. (<b>A</b>–<b>F</b>) Serum TC, TG, LDL-C, HDL-C, ADPN, and LPS levels. (<b>G</b>–<b>J</b>) Hepatic TC, TG, LDL-C, and HDL-C levels. Data are expressed as mean ± SD (<span class="html-italic">n</span> = 8 per group). One-way ANOVA followed by Tukey’s multiple comparisons test were performed for all groups. # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, and ### <span class="html-italic">p</span> &lt; 0.001, versus the ND mice. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 and ns indicates no significant difference, versus the HFD mice.</p>
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<p>Effects of PTP on glucose tolerance (OGTT) and insulin sensibility test (IST) in HFD-fed mice. (<b>A</b>) OGTT. (<b>B</b>) IST. (<b>C</b>,<b>D</b>) Areas under the curve (AUCs) for OGTT and IST. Data are expressed as mean ± SD (<span class="html-italic">n</span> = 8 per group). One-way ANOVA followed by Tukey’s multiple comparisons test for were performed for all groups. ### <span class="html-italic">p</span> &lt; 0.001, versus the ND mice. * <span class="html-italic">p</span> &lt; 0.05, versus the HFD mice using Tukey’s multiple comparisons test for all groups. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Expression of thermogenic protein UCP1 in inguinal white adipose tissue (iWAT) and brown adipose tissue (BAT), and original magnification 400×. (<b>A</b>) iWAT. (<b>B</b>) BAT. (<b>C</b>) Score of immunohistochemical analysis (<span class="html-italic">n</span> = 8 per group). ### <span class="html-italic">p</span> &lt; 0.001, versus the ND mice. ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001, versus the HFD mice.</p>
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<p>Effects of PTP on intestinal microflora structure of mice fed with HFD. (<b>A</b>) Venn diagram of bacteria detected at the ASV level. (<b>B</b>,<b>C</b>) Beta diversity analysis of intestinal microbiota using the non-metric multidimensional scaling (NMDS) and principal co-ordinates analysis (PCoA). (<b>D</b>) LEfSe analysis of microbiota. (<b>E</b>) Bacterial community at the phylum level.</p>
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<p>Effect of PTP on the abundance of intestinal flora in HFD-fed mice. (<b>A</b>) Relative abundance of <span class="html-italic">Faecalibaculum</span> at the genus level. (<b>B</b>) Relative abundance of <span class="html-italic">Romboutsia</span> at the genus level. (<b>C</b>) Relative abundance of <span class="html-italic">Enterorhabdus</span> at the genus level. (<b>D</b>) Relative abundance of <span class="html-italic">norank-f-Muribaculaceae</span> at the genus level. (<b>E</b>) Relative abundance of <span class="html-italic">Firmicutes</span> at the phylum level. (<b>F</b>) Relative abundance of <span class="html-italic">Bacteroidota</span> at the phylum level. (<b>G</b>) Heatmap comparison and hierarchical clustering dendrogram based on the relative abundance at the genus level. One-way ANOVA followed. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001, versus the HFD mice.</p>
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22 pages, 7966 KiB  
Article
P38α MAPK Coordinates Mitochondrial Adaptation to Caloric Surplus in Skeletal Muscle
by Liron Waingerten-Kedem, Sharon Aviram, Achinoam Blau, Tony Hayek and Eyal Bengal
Int. J. Mol. Sci. 2024, 25(14), 7789; https://doi.org/10.3390/ijms25147789 - 16 Jul 2024
Viewed by 711
Abstract
Excessive calorie intake leads to mitochondrial overload and triggers metabolic inflexibility and insulin resistance. In this study, we examined how attenuated p38α activity affects glucose and fat metabolism in the skeletal muscles of mice on a high-fat diet (HFD). Mice exhibiting diminished p38α [...] Read more.
Excessive calorie intake leads to mitochondrial overload and triggers metabolic inflexibility and insulin resistance. In this study, we examined how attenuated p38α activity affects glucose and fat metabolism in the skeletal muscles of mice on a high-fat diet (HFD). Mice exhibiting diminished p38α activity (referred to as p38αAF) gained more weight and displayed elevated serum insulin levels, as well as a compromised response in the insulin tolerance test, compared to the control mice. Additionally, their skeletal muscle tissue manifested impaired insulin signaling, leading to resistance in insulin-mediated glucose uptake. Examination of muscle metabolites in p38αAF mice revealed lower levels of glycolytic intermediates and decreased levels of acyl-carnitine metabolites, suggesting reduced glycolysis and β-oxidation compared to the controls. Additionally, muscles of p38αAF mice exhibited severe abnormalities in their mitochondria. Analysis of myotubes derived from p38αAF mice revealed reduced mitochondrial respiratory capacity relative to the myotubes of the control mice. Furthermore, these myotubes showed decreased expression of Acetyl CoA Carboxylase 2 (ACC2), leading to increased fatty acid oxidation and diminished inhibitory phosphorylation of pyruvate dehydrogenase (PDH), which resulted in elevated mitochondrial pyruvate oxidation. The expected consequence of reduced mitochondrial respiratory function and uncontrolled nutrient oxidation observed in p38αAF myotubes mitochondrial overload and metabolic inflexibility. This scenario explains the increased likelihood of insulin resistance development in the muscles of p38αAF mice compared to the control mice on a high-fat diet. In summary, within skeletal muscles, p38α assumes a crucial role in orchestrating the mitochondrial adaptation to caloric surplus by promoting mitochondrial biogenesis and regulating the selective oxidation of nutrients, thereby preventing mitochondrial overload, metabolic inflexibility, and insulin resistance. Full article
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<p>p38α<sup>AF</sup> mice presented worse metabolic parameters than control mice. (<b>A</b>) Six-week-old mice were fed with ND or an HFD for 10 weeks, and GC muscles were isolated (<span class="html-italic">n</span> = 5) from the control and p38α<sup>AF</sup> mice. Protein lysates from three of the mice per treatment were randomly analyzed by Western blotting with the designated antibodies. α Tubulin was used as the loading control. The quantification of relative p38α phosphorylation is presented in the histogram. (<b>B</b>) The mice underwent the diets described in (A), and the weight of each mouse was measured weekly (<span class="html-italic">n</span> = 5). The graphs represent the average percent change in the body weight of the two mouse groups (control and p38α<sup>AF</sup>), which were fed with ND or HFD. The weight was set to 100 on the first day of the diet. (<b>C</b>) The hematological parameters of control mice and p38α<sup>AF</sup> on an HFD. The glucose and cholesterol levels were measured in the serum of control and p38α<sup>AF</sup> mice after 10 weeks on an HFD (AML-central lab services). Insulin was measured (<span class="html-italic">n</span> = 3) using an ELISA kit (Millipore RAB0817). The significance probabilities between treatments were designated as numbers. (<b>D</b>) Insulin tolerance test (ITT): the graph displays the relative average glucose levels at 0, 30, 45, 60, 90, and 120 min following insulin injection (0.5 U/kg BW) in the blood of control and p38α<sup>AF</sup> mice after a 10-week HFD (<span class="html-italic">n</span> = 4 mice per group). The mice were deprived of chaw for 6 h before insulin was IP-injected. The glucose level before insulin injection was set to 100 percent, and all values were relative to 100. Data are presented as the mean ± SE. One-way ANOVA was followed by Tukey post-tests (<b>A</b>), two-way ANOVA was followed by Bonferroni post-tests (<b>B</b>,<b>D</b>) and a Student t-test (<b>C</b>). The <span class="html-italic">p</span> values for group difference are designated as follows: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Block of the insulin-mediated 2 deoxy-glucose (2DG) uptake by the Tibialis muscle of p38α<sup>AF</sup> mice. (<b>A</b>) Experimental layout: saline or insulin (1 unit/kg) was IP-injected following a 3 h fasting of the mice previously fed with an HFD for 10 weeks. Ten min later, 5% 2DG was IP-injected (10 μL to 1 g weight). The mice were sacrificed one hour later, and the Tibialis muscles were frozen and used in the mass spectrometry (MS) analysis of metabolites, or to extract proteins for Western blotting analysis. (<b>B</b>) Peak area were analyzed by the MS values of 2- Deoxy –D Glucose (<span class="html-italic">n</span> = 4) that were normalized to mg tissue. (<b>C</b>) Protein extracts from the Tb muscles (<span class="html-italic">n</span> = 3) were analyzed by Western blotting with antibodies directed to phosphorylated Akt (Serine 473) and Pan Akt. Quantification of the relative phosphorylation (pAkt/Akt) is presented in the histogram. Data are presented as the mean ± SE. The Wilcoxon test and significance probabilities between treatments are designated as numbers in (<b>B</b>). One-way ANOVA was followed by Tukey post-tests. The <span class="html-italic">p</span> values for group difference are designated as follows: * <span class="html-italic">p</span> &lt; 0.05 (<b>C</b>).</p>
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<p>Reduced glycolytic metabolites and increased lactate-to-pyruvate ratio in the muscles of HFD-fed p38α<sup>AF</sup> mice. Extracted metabolites from the Tibialis muscles of 10-week HFD-fed mice that were IP-injected without or with insulin (<span class="html-italic">n</span> = 4). (<b>A</b>) The normalized peak areas (to mg tissue) that were analyzed by the MS of several glycolytic metabolites. (<b>B</b>) The normalized peak areas (to mg tissue) that were analyzed by the MS of pyruvate, lactate, and the ratio of lactate to pyruvate. (<b>C</b>) Analysis of the expression and the phosphorylation on serine 293 of the E1 subunit of pyruvate dehydrogenase (PDH) in the Tb muscles of control and p38α<sup>AF</sup> mice (<span class="html-italic">n</span> = 5) by Western blotting using antibodies to phospho-PDH (Ser293) and PDH. The quantification of relative phosphorylation (pPDH/PDH) is presented in the histogram. Data are presented as the mean ± SE. The Wilcoxon test and significance probabilities between treatments are designated as numbers in (<b>B</b>).</p>
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<p>Reduced β oxidation in the muscles of p38α<sup>AF</sup> mice relative to the muscles of control mice following a high-fat diet. Metabolites were extracted from the Tibialis muscles of 10-week HFD-fed mice that were IP-injected without or with insulin (<span class="html-italic">n</span> = 4). (<b>A</b>) The peak areas (normalized to mg tissue) of glycerol analyzed by MS are presented. (<b>B</b>) Analysis of the mRNA levels of FABP3 in the muscles of control and p38α<sup>AF</sup> mice by qPCR (<span class="html-italic">n</span> = 5). The β-actin housekeeping gene was used to normalize the mRNA levels. (<b>C</b>) Analysis of the mRNA levels of ACC2 in the muscles of control and p38α<sup>AF</sup> mice by qPCR (<span class="html-italic">n</span>= 4). The β-actin housekeeping gene was used to normalize mRNA levels. (<b>D</b>) Analysis of the expression and the phosphorylation on serine 212 of Acetyl CoA Carboxylase 2 (ACC2) in the muscles of control and p38α<sup>AF</sup> mice (<span class="html-italic">n</span> = 5) by Western blotting using antibodies to phospho-ACC2 (Ser212), ACC2, and αTubulin (which served as a loading control). The histograms present the relative expression of ACC2 (ACC2/Tubulin) and relative ACC2 phosphorylation on serine 212 (pACC2/ACC2). (<b>E</b>) The peak areas (normalized to mg tissue) of acyl-carnitines are presented. Values represent the means ± SEM. The Wilcoxon test and significance probabilities between treatments are designated as numbers (<b>A</b>,<b>E</b>). One-way ANOVA followed by Tukey post-tests (<b>B</b>,<b>C</b>). The <span class="html-italic">p</span> values for group difference are designated as follows: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Severe mitochondrial defects in the muscles of p38α<sup>AF</sup> mice. (<b>A</b>) Transmission electron microscopy (TEM) analysis of the representative muscles from control and p38α<sup>AF</sup> mice fed with NDs and HFDs. The Tibialis muscles were isolated, and longitudinal sections were processed for TEM analysis (see <a href="#sec4dot10-ijms-25-07789" class="html-sec">Section 4.10</a>). Representative images are shown. Scale bar: 1 μm. Asterisks are adjacent to the mitochondria (<b>B</b>) Analysis of the mRNA levels of PGC1α in the muscles of control and p38α<sup>AF</sup> mice fed with NDs and HFDs by qPCR (<span class="html-italic">n</span> = 5). The β-actin housekeeping gene was used to normalize the mRNA levels. Data represent the means ± SEM. One-way ANOVA was followed by Tukey post-tests (B). The <span class="html-italic">p</span> values for group differences are designated as follows: * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Biochemical and metabolic analysis of the myotubes derived from control and p38α<sup>AF</sup> mice. (<b>A</b>) p38 MAPK phosphorylation: Myotubes were grown for 24 h in the absence or presence of 0.4 mM of palmitate. Insulin (10 μg/mL) was added 30 min before the proteins were extracted and analyzed by Western blotting using the designated antibodies. (<b>B</b>) Insulin signaling pathway: The same protein samples as in (A) were analyzed by Western blotting using the designated antibodies. (<b>C</b>) Metabolism of the (U-<sup>13</sup>C<sub>6</sub>) glucose in myotubes: (U-<sup>13</sup>C<sub>6</sub>) glucose was introduced to the myotube media with or without 0.4 mM of palmitate for 24 h. The relative levels of glucose 6-phosphate (+6), fructose 6-phosphate (+6), and ribose phosphate (+5) isotopologues are presented. The peak area was normalized to protein concentration. (<b>D</b>) Medium acidification (ECAR) of myotubes in a “Seahorse” analysis: Myotubes were grown in glucose, or glucose and palmitate, for 24 h before analysis. (<b>E</b>) Metabolism of the (U-<sup>13</sup>C<sub>6</sub>) glucose in myotubes: The relative levels of the isotopologues of citrate are presented. The peak areas were normalized to protein concentration. (<b>F</b>) Mitochondrial enzymes: The same protein samples as in (A) were analyzed by Western blotting. The histograms present the relative expression and phosphorylation of PDH (Ser293), and the expression of citrate synthase. Data represent the means ± SEM. The Wilcoxon test and significance probabilities between treatments are designated as follows: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 (<b>C</b>,<b>E</b>). One-way ANOVA was followed by Tukey post-tests (<b>D</b>). The <span class="html-italic">p</span> values for group differences are designated as follows: * <span class="html-italic">p</span> &lt; 0.05 and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Metabolism of palmitate in the myotubes derived from control and p38α<sup>AF</sup> mice. Myotubes were grown in a low-glucose DMEM supplemented with 0.4 mM of palmitate-<sup>13</sup>C<sub>16</sub> for 6 and 24 h. (<b>A</b>) The peak area (normalized to protein concentration) of palmitate (+16), the isotopologues of the TCA cycle, and the derived amino acids that originated from palmitate-<sup>13</sup>C<sub>16.</sub> FC: fold change in the palmitate derived (<sup>13</sup>C ≥ 2) metabolite abundance relative to a WT of 6 h or WT of 24 h. Dashed arrows indicate of missing stages in the TCA-cycle. (<b>B</b>) Myotubes were grown for 24 h in the absence or presence of 0.4 mM of palmitate. Insulin (10 μg/mL) was added 30 min before proteins were extracted and analyzed by Western blotting with the designated antibodies. The histograms present the relative expression of ACC2, the phosphorylation of ACC2 (Ser212), and the phosphorylation of AMPKα (Thr172). (<b>C</b>) The oxygen consumption rate (OCR) at the maximal respiration of myotubes that were grown on glucose, or glucose and palmitate, for 24 h. (<b>D</b>) Comparison of the mitochondrial membrane electrochemical potential in myotubes that were grown on glucose, or glucose and palmitate, for 24 h. JC-1 dye was used to monitor the mitochondrial membrane potential. FCCP disrupts the mitochondrial membrane potential. Data represent the means ± SEM. One-way ANOVA was followed by Tukey post-tests (<b>A</b>,<b>C</b>). The <span class="html-italic">p</span> values for group difference are designated as follows: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>A model for the role of p38α in insulin sensitivity. In the left panel, a high-fat diet activates p38α in wild-type mice, leading to an increased expression and activity of PGC1α and ACC2 in the skeletal muscles. PGC1α acts as a co-activator, increasing mitochondrial biogenesis and activity, while ACC2 regulates fatty acid transport into mitochondria. These activities of p38α help coordinate glucose and fat oxidation, preserving metabolic flexibility and preventing mitochondrial damage. Under these conditions, both energy balance and insulin sensitivity are preserved.</p>
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17 pages, 3019 KiB  
Article
Role of Brown Adipose Tissue in Metabolic Health and Efficacy of Drug Treatment for Obesity
by Natalia O. Markina, Georgy A. Matveev, German G. Zasypkin, Tatiana I. Golikova, Daria V. Ryzhkova, Yulia A. Kononova, Sergey D. Danilov and Alina Yu. Babenko
J. Clin. Med. 2024, 13(14), 4151; https://doi.org/10.3390/jcm13144151 - 16 Jul 2024
Viewed by 953
Abstract
(1) Background: Brown adipose tissue (BAT) is responsible for non-shivering thermogenesis, and its activation has become a new object as both a determinant of metabolic health and a target for therapy. This study aimed to identify the relationships between the presence of [...] Read more.
(1) Background: Brown adipose tissue (BAT) is responsible for non-shivering thermogenesis, and its activation has become a new object as both a determinant of metabolic health and a target for therapy. This study aimed to identify the relationships between the presence of BAT, parameters that characterize metabolic health (glucose, lipids, blood pressure (BP)), and the dynamics of body mass index (BMI) during weight-reducing therapy. (2) Methods: The study included 72 patients with obesity. We investigated metabolic parameters, anthropometric parameters, and BP. Dual-energy X-ray absorptiometry (DXA) and positron emission tomography and computed tomography (PET/CT) imaging with 18F-fluorodeoxyglucose (18F-FDG) were performed. (3) Results: Before weight-reducing therapy, BAT was revealed only in 19% patients with obesity. The presence of BAT was associated with a lower risk of metabolic deviations that characterize metabolic syndrome: shorter waist circumference (WC) (p = 0.02) and lower levels of glucose (p = 0.03) and triglycerides (p = 0.03). Thereafter, patients were divided into four groups according to the type of therapy (only lifestyle modification or with Liraglutide or Reduxin or Reduxin Forte). We did not find a relationship between the presence of BAT and response to therapy: percent weight reduction was 10.4% in patients with BAT and 8.5% in patients without BAT (p = 0.78) during six months of therapy. But we noted a significant positive correlation between the volume of BAT and the effectiveness of weight loss at 3 months (r = 0.52, p = 0.016). The dynamic analysis of BAT after 6 months of therapy showed a significant increase in the volume of cold-induced metabolically active BAT, as determined by PET/CT with 18F-FDG in the Liraglutide group (p = 0.04) and an increase in the activity of BAT standardized uptake value (SUV mean and SUV max) in the Reduxin (p = 0.02; p = 0.01, respectively) and Liraglutide groups (p = 0.02 in both settings). (4) Conclusions: The presence of brown adipose tissue is associated with a lower risk of metabolic abnormalities. In general, our study demonstrated that well-established drugs in the treatment of obesity (Liraglutide and Reduxin) have one more mechanism for implementing their effects. These drugs have the ability to increase the activity of BAT. A significant positive relationship between the total volume of BAT and the percentage of weight loss may further determine the priority mechanism of the weight-reducing effect of these medicaments. Full article
(This article belongs to the Topic Metabolic Syndrome, Biomarkers and Lifestyles)
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<p>Dynamics of weight loss percentage in patients with and without BAT (<b>A</b>). Trend in weight loss in kilograms in patients with BAT versus without BAT (<b>B</b>).</p>
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<p>Changes in triglyceride lowering after 6 months of therapy in patients with BAT versus without BAT. Abbreviations: BAT—brown adipose tissue, TG—triglycerides.</p>
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<p>Percentage weight loss in patients with BAT versus without BAT in lifestyle modification group (<b>A</b>). Weight loss in kilograms in patients with and without BAT in lifestyle modification group (<b>B</b>).</p>
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<p>Percentage weight loss in patients with BAT versus without BAT who received Reduxin (<b>A</b>). Weight loss in kilograms in patients with and without BAT who received Reduxin (<b>B</b>).</p>
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22 pages, 2053 KiB  
Review
A Comparative Assessment of the Pathogenic Potential of Newly Discovered Henipaviruses
by Kristina Meier, Judith Olejnik, Adam J. Hume and Elke Mühlberger
Pathogens 2024, 13(7), 587; https://doi.org/10.3390/pathogens13070587 - 16 Jul 2024
Viewed by 990
Abstract
Recent advances in high-throughput sequencing technologies have led to the discovery of a plethora of previously unknown viruses in animal samples. Some of these newly detected viruses are closely related to human pathogens. A prime example are the henipaviruses. Both Nipah (NiV) and [...] Read more.
Recent advances in high-throughput sequencing technologies have led to the discovery of a plethora of previously unknown viruses in animal samples. Some of these newly detected viruses are closely related to human pathogens. A prime example are the henipaviruses. Both Nipah (NiV) and Hendra virus (HeV) cause severe disease in humans. Henipaviruses are of zoonotic origin, and animal hosts, including intermediate hosts, play a critical role in viral transmission to humans. The natural reservoir hosts of NiV and HeV seem to be restricted to a few fruit bat species of the Pteropus genus in distinct geographic areas. However, the recent discovery of novel henipa- and henipa-like viruses suggests that these viruses are far more widespread than was originally thought. To date, these new viruses have been found in a wide range of animal hosts, including bats, shrews, and rodents in Asia, Africa, Europe, and South America. Since these viruses are closely related to human pathogens, it is important to learn whether they pose a threat to human health. In this article, we summarize what is known about the newly discovered henipaviruses, highlight differences to NiV and HeV, and discuss their pathogenic potential. Full article
(This article belongs to the Collection Emerging and Re-emerging Pathogens)
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<p>The global distribution and phylogenetic tree of henipa- and henipa-like viruses. (<b>A</b>) Countries in which viral genomes or genome fragments with homology to henipaviruses have been reported are indicated in blue. Black animal icons indicate viral RNA-positive samples. Red animal icons indicate outbreaks of human disease. The yellow animal icon represents the discovery of MojV, for which the association with human disease remains unclear. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>. (<b>B</b>) A phylogenetic tree of henipa- and henipa-like viruses using the protein coding sequence of all viral genes. Generated with Geneious Prime. Sequences of the V and W proteins shared in common with the P gene (i.e., N-terminal to the mRNA editing site) were removed to prevent over-representation of this sequence, whereas the sequence for the X protein for Ninorex virus was included due to the flanking transcription start and end signals. The S protein sequences were excluded from this analysis since they are currently only hypothetical and do not contain flanking transcriptional regulatory sequences. Viruses found in bats are in red, viruses found in an opossum in brown, viruses found in shrews in blue, and viruses found in rodents in purple. The scale bar represents nucleotide substitutions per site. Nipah virus Bangladesh strain (NiV-B, AY988601.1), Nipah virus Malaysia strain (NiV-M, NC_002728.1) Hendra virus genotype 1 (HeV-g1, AF017149.3), Hendra virus genotype 2 (HeV-g2, MZ318101.1), Cedar virus (CedV, NC_025351.1), Cedar virus Geelong (CedV-G, KP271122.1), Ghana virus (GhV, NC_025256.1), Angavokely virus (AngV, ON613535.1), Peixe-Boi virus (PBV, MZ615319), Resua virus (ResV, OR713876.1), Gamak virus (GAKV, MZ574407.1), Jingmen <span class="html-italic">Crocidura shantungensis</span> virus (JCsV, OM030314.1), Shiyan <span class="html-italic">Crocidura tanakae</span> virus (SCtV, OQ970176.1), Wufeng <span class="html-italic">Crocidura attenuata</span> virus (WCaV, OM030317.1), Lechodon virus (LechV, OR713879.1), Wenzhou <span class="html-italic">Suncus murinus</span> virus (WSmV, OQ715593.1), Wenzhou <span class="html-italic">Apodemus agrarius</span> virus (WAaV, MZ328275.1), Hasua virus (HasV, OR713881.1), Langya virus (LayV, OM101125.1), Mòjiāng virus (MojV, NC_025352.1), Daeryong virus (DARV, MZ574409.1), Jingmen <span class="html-italic">Crocidura shantungensis 2</span> virus (JCs2V, OM030315.1), Melian virus (MeliV, OK623353.1), Denwin virus (DewV, OK623354.1), Wufeng <span class="html-italic">Chodsigoa smithii</span> virus (WCsV, OM030316.1), Sichuan <span class="html-italic">Chodsigoa hypsibia</span> virus (SChV, OQ236120.1), and Ninorex virus (NinExV, OQ438286.1) are included.</p>
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<p>Henipavirus genome organization. (<b>A</b>) Schematic diagrams of select henipavirus and henipa-like virus genomes are depicted to scale. Leader and trailer sequences are indicated by black bars, with missing sequence information indicated by squiggly lines (not to scale). Genes are depicted as colored bars with lighter portions indicating open reading frames (ORFs). Additional ORFs encoded by the P gene are depicted above the P gene. Sites of co-transcriptional mRNA editing in the P gene are indicated by arrows underneath the P gene and by lines within the V and W ORFs. N, nucleocapsid protein; P, phosphoprotein; C, V, W, accessory proteins encoded by the P gene; M, matrix protein; X, putative protein of unknown function; S, putative small transmembrane protein encoded within the 5′ UTR of the F gene; F, fusion glycoprotein; G, attachment glycoprotein; and L, RNA-dependent RNA polymerase. (<b>B</b>) Nucleotide frequency plot of the bipartite promoter regions located at the viral genome and antigenome ends based on a sequence comparison of 24 henipaviruses and henipa-like viruses. The viral genome and antigenome sequences are depicted in hexamers, and the number of each hexamer is shown above the sequences. The leader region within the genome containing the first promoter element spans nucleotides 1 to 52. The conserved gene start signal of the N gene spans nucleotides 53 to 60. The second promoter element spans hexamers 14 to 16 with the first C residue of each hexamer being conserved (indicated by arrows).</p>
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<p>A comparison of the known entry receptors for henipaviruses. NiV and HeV G use ephrin-B2 and, to a lesser extent in the case of HeV, ephrin-B3 as entry receptors. GhV G binds to ephrin-B2 but not -B3. CedV G binds to human ephrin-B1, -B2, -A2, -A5 and murine ephrin-A1. The entry receptors of bat-borne AngV as well as henipa-like viruses within the shrew- and rodent-borne clade are currently unknown. While G recognizes and binds to the cellular entry receptor, both G and F glycoproteins are required for viral and host cell membrane fusion. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Tools used to study the different steps of the henipavirus replication cycle. The first step of the henipavirus replication cycle is G-mediated attachment and binding to the cellular receptor (e.g., ephrin-B2 or -B3). Fusion of the viral membrane with the cell membrane occurs at the cell surface and is mediated by a concerted effort of both G and F. The helical nucleocapsid complex is then released into the cytoplasm of the infected cell where primary transcription is initiated. The viral mRNAs are translated, leading to secondary transcription and viral genome replication. Replication takes place in cytoplasmic viral inclusion bodies. Some of the viral proteins, including P, V, W, and C, modulate antiviral host responses. Together with N, P, and L, the newly synthesized viral genomes are packaged into nucleocapsids and transported to the plasma membrane for viral particle assembly. Budding and viral particle release is mediated by M. The depiction of the henipavirus replication cycle was inspired by [<a href="#B146-pathogens-13-00587" class="html-bibr">146</a>]. Tools used to study the various steps of the henipavirus replication cycle are indicated in the blue boxes. F, fusion glycoprotein; G, attachment glycoprotein; L, RNA-dependent RNA polymerase; M, matrix protein; N, nucleocapsid protein; P, phosphoprotein; trVLPs, transcription- and replication-competent virus-like particles; and VLPs, virus-like particles. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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15 pages, 3274 KiB  
Article
Carnosic Acid (CA) Induces a Brown Fat-like Phenotype, Increases Mitochondrial Biogenesis, and Activates AMPK in 3T3-L1 Adipocytes
by Filip Vlavcheski, Rebecca E. K. MacPherson, Val Fajardo, Newman Sze and Evangelia Tsiani
Biomedicines 2024, 12(7), 1569; https://doi.org/10.3390/biomedicines12071569 - 15 Jul 2024
Viewed by 727
Abstract
Adipose tissue plays a crucial role in regulating metabolic homeostasis, and its dysfunction in obesity leads to insulin resistance and type 2 diabetes (T2D). White adipose tissue (WAT) primarily stores energy as lipids, while brown adipose tissue (BAT) regulates thermogenesis by dissipating energy [...] Read more.
Adipose tissue plays a crucial role in regulating metabolic homeostasis, and its dysfunction in obesity leads to insulin resistance and type 2 diabetes (T2D). White adipose tissue (WAT) primarily stores energy as lipids, while brown adipose tissue (BAT) regulates thermogenesis by dissipating energy as heat. The process of browning involves the transdifferentiation of WAT into brown-like or beige adipocytes, which exhibit a similar phenotype as BAT. The browning of WAT is an attractive approach against obesity and T2D, and the activation of the energy sensor AMP-activated protein kinase (AMPK) has been shown to play a role in browning. Carnosic acid (CA), a polyphenolic diterpene, found in many plants including rosemary, is reported to possess potent antioxidant, anti-inflammatory, and anti-hyperglycemic properties. The limited evidence available indicates that CA activates AMPK and may have anti-obesity and antidiabetic potential; however, the effects in adipocyte browning remain largely unexplored. This study aimed to examine the effects of CA on the markers of adipocyte browning. The treatment of 3T3L1 adipocytes with CA activated AMPK, reduced lipid accumulation, and increased the expression of browning protein markers (UCP-1, PGC-1α, PRDM16, and TFAM) and mitochondrial biogenesis. The use of compound C, an AMPK inhibitor, significantly attenuated the effects of CA, indicating AMPK involvement. These studies demonstrate that CA can activate AMPK and stimulate the browning of white adipocytes. Future animal and human studies are required to examine the effects of CA in vivo. Full article
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Figure 1
<p>Effects of CA on 3T3-L1 adipocyte lipid content. Fully differentiated 3T3-L1 adipocytes were pretreated for 1 h without (C) or with CC (25 mM), followed by a treatment without (C) or with CA (10 μM) or MET (5 mM) for 24 h in serum-deprived media. After treatment: (<b>A</b>) The cells were stained with Oil Red O (ORO) and microscopic images were taken using the color field filter on a Cytation Gen5 multimode imaging microscope (×20). (<b>B</b>) Oil Red O was extracted from the cells and the intensity of the supernatant was measured at 490 nm using an ELISA plate reader. (<b>C</b>) Fully differentiated 3T3-L1 adipocytes were treated with CA (10 μM), β<sub>3</sub>-adrenergic agonist (CL 316 243) (1 μM), or the PPARγ activator rosiglitazone (ROSI) (10 μM) for 24 h followed by ORO stain and absorbance measurements. The results are the mean ± standard error (SE) of four to six independent experiments, expressed as a percent of the control: ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control and ### <span class="html-italic">p</span> &lt; 0.001, as indicated.</p>
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<p>Effects of CA on mitochondrial density: Fully differentiated 3T3-L1 adipocytes were treated without (C) or with CA (10 μM) in the presence or absence of CC for 24 h followed by exposure to 250 nM MitoTracker reagent and 2.5 mg/mL Hoechst blue for 30 min. The cells were then fixed and visualized with Cytation5 using TexasRed (abs/em 644/665 nm) and DAPI/Hoechst filter. Pictures of the plate were taken automatically at the same time using the Cytation5 recommended protocol using the Hoechst/DAPI filter to detect the nuclei (<b>A</b>). The intensity of the red florescence was expressed in arbitrary units (<b>B</b>). Hoechst blue images were merged with the MitoTracker Red and pictures were created. The data are the mean ± SE of five to six separate experiments. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control, # <span class="html-italic">p</span> &lt; 0.05, and ### <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>CA and MET increase AMPK and ACC phosphorylation in 3T3-L1 adipocytes. Fully differentiated 3T3-L1 adipocytes were incubated without (C) or with carnosic acid (CA) (10 μM) or metformin (MET) (5 mM) for 24 h in the absence or presence of compound C (CC) (25 μM). After treatment, the cells were lysed and SDS-PAGE was performed, followed by immunoblotting using specific antibodies to recognize the total and phosphorylated (Thr172) levels of AMPK and ACC. Representative blots are shown (<b>A</b>,<b>B</b>). The densitometry of the bands was measured and expressed in arbitrary units as a percent of the control (<b>C</b>,<b>D</b>). The data are the mean ± SE of seven to eight separate experiments., *** <span class="html-italic">p</span> &lt; 0.001 vs. control, ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001, as indicated.</p>
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<p>Effects of CA on UCP-1 levels. Fully differentiated 3T3-L1 adipocytes were pretreated for 1 h without (C) or with CC (25 mM), followed by treatment without (C) or with CA (10 μM) or MET (5 mM) for 24 h in serum-deprived media. After treatment, the cells are lysed and SDS-PAGE was performed followed by immunoblotting using specific antibodies to recognize the total levels of UCP-1 or β-actin and immunostaining using an anti-UCP-1 primary antibody and AlexaFluor488 secondary antibody. Hoechst blue stain was used to label the nuclei. Representative blots are shown (<b>A</b>). The densitometry of the bands was measured and expressed in arbitrary units as a percent of the control (<b>B</b>). Images were taken with Cytation5, a florescence microscope using Green Florescent Protein (GFP) and DAPI/Hoechst filter (<b>C</b>). The intensity of the green florescence was measured using ImageJ and is expressed in arbitrary units (<b>D</b>). The data are the mean ± SE of six to eleven separate experiments. ** <span class="html-italic">p</span> &lt; 0.01 vs. control, # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, as indicated.</p>
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<p>Effects of CA on browning markers: Fully differentiated 3T3-L1 adipocytes were incubated without (C) or with CA (10 μM) or MET (5 mM) for 24 h in the absence and presence of CC (25 μM). After treatment, the cells are lysed and SDS-PAGE was performed, which was followed by immunoblotting using specific antibodies to recognize the total levels of PPARγ, PRDM18, PGC-1α, TFAM, or β-actin. Representative blots are shown (<b>A</b>). The densitometry of the bands was measured and is expressed in arbitrary units as a percent of the control (<b>B</b>–<b>E</b>). The data are the mean ± SE of seven to nine separate experiments. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. control, # <span class="html-italic">p</span> &lt; 0.05, and ## <span class="html-italic">p</span> &lt; 0.01, as indicated.</p>
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<p>Effects of CA and CC on 3T3-L1 adipocyte viability. (<b>A</b>) Fully differentiated adipocytes were treated without (C) or with a range of CA concentrations (5 to 100 μM) or with their corresponding vehicle (DMSO) concentrations for 24 h followed by incubation with MTT. The formazan dye was then solubilized, and absorbance was measured at 570 nm. Cell viability is expressed as a percent of the control (C) untreated cells (<b>B</b>) Fully differentiated adipocytes were treated without (C) or with CA in the absence or presence of CC for 24 h followed by MTT assay. The dye was solubilized and read at 570 nm. The values were expressed as a percent of the control and are the mean ± SEM of three independent experiments.</p>
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<p>Effects of CA and MET on GSK3β. Fully differentiated 3T3-L1 adipocytes were incubated without (C) or with CA (10 μM) or MET (5 mM) for 24 h in the absence or the presence of CC (25 μM). After the treatment, the cells are lysed and SDS-PAGE was performed, which was followed by immunoblotting using specific antibodies to recognize the total and phosphorylated (Ser9) levels of GSK3β. Representative blots are shown (<b>A</b>). The densitometry of the bands was measured and expressed as a percent of control (<b>B</b>). The data are the mean ± SE of two separate experiments. * <span class="html-italic">p</span> &lt; 0.05, and ## <span class="html-italic">p</span> &lt; 0.01, as indicated.</p>
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<p>CA activated AMPK, inhibited GSK3β, and increased the expression of browning (UCP-1, PRDM16, and PPARγ) and mitochondrial biogenesis protein markers (PGC-1α and TFAM). Use of compound C, an AMPK inhibitor, significantly attenuated the effects of CA. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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22 pages, 1312 KiB  
Article
Host–Virus Cophylogenetic Trajectories: Investigating Molecular Relationships between Coronaviruses and Bat Hosts
by Wanlin Li and Nadia Tahiri
Viruses 2024, 16(7), 1133; https://doi.org/10.3390/v16071133 - 15 Jul 2024
Viewed by 640
Abstract
Bats, with their virus tolerance, social behaviors, and mobility, are reservoirs for emerging viruses, including coronaviruses (CoVs) known for genetic flexibility. Studying the cophylogenetic link between bats and CoVs provides vital insights into transmission dynamics and host adaptation. Prior research has yielded valuable [...] Read more.
Bats, with their virus tolerance, social behaviors, and mobility, are reservoirs for emerging viruses, including coronaviruses (CoVs) known for genetic flexibility. Studying the cophylogenetic link between bats and CoVs provides vital insights into transmission dynamics and host adaptation. Prior research has yielded valuable insights into phenomena such as host switching, cospeciation, and other dynamics concerning the interaction between CoVs and bats. Nonetheless, a distinct gap exists in the current literature concerning a comparative cophylogenetic analysis focused on elucidating the contributions of sequence fragments to the co-evolution between hosts and viruses. In this study, we analyzed the cophylogenetic patterns of 69 host–virus connections. Among the 69 host–virus links examined, 47 showed significant cophylogeny based on ParaFit and PACo analyses, affirming strong associations. Focusing on two proteins, ORF1ab and spike, we conducted a comparative analysis of host and CoV phylogenies. For ORF1ab, the specific window ranged in multiple sequence alignment (positions 520–680, 770–870, 2930–3070, and 4910–5080) exhibited the lowest Robinson–Foulds (RF) distance (i.e., 84.62%), emphasizing its higher contribution in the cophylogenetic association. Similarly, within the spike region, distinct window ranges (positions 0–140, 60–180, 100–410, 360–550, and 630–730) displayed the lowest RF distance at 88.46%. Our analysis identified six recombination regions within ORF1ab (positions 360–1390, 550–1610, 680–1680, 700–1710, 2060–3090, and 2130–3250), and four within the spike protein (positions 10–510, 50–560, 170–710, and 230–730). The convergence of minimal RF distance regions with combination regions robustly affirms the pivotal role of recombination in viral adaptation to host selection pressures. Furthermore, horizontal gene transfer reveals prominent instances of partial gene transfer events, occurring not only among variants within the same host species but also crossing host species boundaries. This suggests a more intricate pattern of genetic exchange. By employing a multifaceted approach, our comprehensive strategy offers a nuanced understanding of the intricate interactions that govern the co-evolutionary dynamics between bat hosts and CoVs. This deeper insight enhances our comprehension of viral evolution and adaptation mechanisms, shedding light on the broader dynamics that propel viral diversity. Full article
(This article belongs to the Special Issue Bat- and Rodent-Borne Zoonotic Viruses)
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<p>Tanglegram of cophylogenetic relationships between bat host and coronaviruses. Maximum likelihood phylogenies for coronaviruses (<b>left side</b>) and their bat hosts (<b>right side</b>), with bootstrap support values ≥75 labeled. All host–pathogen associations are shown in the tanglegram as dark yellow and black connecting lines. Black lines indicate significant individual cospeciation links between coronaviruses and their hosts, as indicated by both ParaFit and PACo (<span class="html-italic">p</span>-value ≤ 0.05), while dark yellow lines represent non–significant links.</p>
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<p>Cytochrome b (cytb) gene similarity and phylogenetic tree between <span class="html-italic">Rhinolophus affinis</span> and six other bat species: (<b>a</b>) SimPlot sliding window analysis of cytochrome b (cytb) gene similarity between <span class="html-italic">Rhinolophus affinis</span> and six other bat species; (<b>b</b>) cytochrome b (cytb) gene phylogenetic tree of seven bat species. Species clusters are indicated on the right. The seven–leaf tree was inferred using the RAxML method. To enable direct comparison with the coronavirus (CoV) tree, the branches of the original tree were meticulously duplicated for each bat species leaf, mirroring the count of collected CoV variants, and subsequently relabeled utilizing CoV variant descriptors. These labels integrate virus and host particulars with a hyphen, encompassing the NCBI genome accession number of the virus and its cytochrome b (cytb) gene accession number of host (Virus ID–Host ID).</p>
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<p>Fluctuation of normalized Robinson–Foulds (RF) distance across multiple sequence alignment (MSA) in phylogenetic trees: comparing coronavirus ORF1ab amino acids and bat cytochrome b (cytb) gene. The X–axis indicates the start position of sliding windows on the MSA.</p>
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<p>Dynamic sequence similarity patterns of ORF1ab amino acid sequences: (<b>a</b>) SimPlot sliding window analysis between coronaviruses from <span class="html-italic">Rhinolophus affinis</span> and six other bat species; and (<b>b</b>) sequence similarity network with global similarity threshold of 75%.</p>
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<p>Fluctuation of normalized Robinson–Foulds (RF) distance across multiple sequence alignment (MSA) in phylogenetic trees: Comparing coronavirus spike amino acids and bat cytochrome b (cytb) gene. The X–axis indicates the start position of sliding windows on the MSA.</p>
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<p>Dynamic sequence similarity patterns of spike amino acid sequences: (<b>a</b>) SimPlot sliding window analysis between coronaviruses from <span class="html-italic">Rhinolophus affinis</span> and six other bat species; and (<b>b</b>) sequence similarity network with global similarity threshold of 75%.</p>
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<p>Putative horizontal gene transfer events found for the window regions of ORF1ab amino acid sequences of 47 CoV variants. The left segment of each figure section displays the tree generated from significant recombination regions, while the corresponding right section depicts the species tree (referred to as the whole genome tree) wherein statistically significant horizontal gene transfers (HGT) are graphically represented using arrows to indicate transfer directions. The figure shows 6 significant recombination regions: panel (<b>a</b>) between 360 and 1390 residues, panel (<b>b</b>) between 550 and 1610 residues, panel (<b>c</b>) between 360 and 1680 residues, panel (<b>d</b>) between 700 and 1710 residues, panel (<b>e</b>) between 2060 and 3090 residues, and panel (<b>f</b>) between 2130 and 3250 residues. CoV variant labels integrate virus and host particulars with a hyphen, encompassing the NCBI genome accession number of the virus and its cytochrome b (cytb) gene accession number of the host (Virus ID–Host ID). Distinct hosts are distinguished by various colors: AB085735 signifies <span class="html-italic">Miniopterus fuliginosus</span> in red; ON640726 represents <span class="html-italic">Miniopterus magnater</span> in maroon; KP972690 corresponds to <span class="html-italic">Rhinolophus affinis</span> in magenta; HM134917 denotes <span class="html-italic">Rhinolophus sinicus</span> in blue; KX261916 signifies <span class="html-italic">Rhinolophus macrotis</span> in gray; MZ936290 corresponds to <span class="html-italic">Rhinolophus blasii</span> in aqua; and ON012504 stands for <span class="html-italic">Rhinolophus pusillus</span> in mauve.</p>
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<p>Putative horizontal gene transfer events found for the window regions of spike amino acid sequences of 47 CoV variants. The left segment of each figure section displays the tree generated from significant recombination regions, while the corresponding right section depicts the species tree (referred to as the whole genome tree) wherein statistically significant horizontal gene transfers are graphically represented using arrows to indicate transfer directions. The figure shows 4 significant recombination regions: panel (<b>a</b>) between 10 and 510 residues, panel (<b>b</b>) between 50 and 560 residues, panel (<b>c</b>) between 170 and 710 residues, and panel (<b>d</b>) between 230 and 730 residues. CoV variant labels integrate virus and host particulars with a hyphen, encompassing the NCBI genome accession number of virus and its cytochrome b (cytb) gene accession number of host (Virus ID–Host ID). Distinct hosts are distinguished by various colors: AB085735 signifies <span class="html-italic">Miniopterus fuliginosus</span> in red; ON640726 represents <span class="html-italic">Miniopterus magnater</span> in maroon; KP972690 corresponds to <span class="html-italic">Rhinolophus affinis</span> in magenta; HM134917 denotes <span class="html-italic">Rhinolophus sinicus</span> in blue; KX261916 signifies <span class="html-italic">Rhinolophus macrotis</span> in gray; MZ936290 corresponds to <span class="html-italic">Rhinolophus blasii</span> in aqua; and ON012504 stands for <span class="html-italic">Rhinolophus pusillus</span> in mauve.</p>
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