Personal historical perspective of HIV: part 11.

All animal life on earth is thought to have a common origin and have common genetic mechanisms. Evolution has enabled differentiation of species. Pathogens likewise have evolved within various species and mostly come to a settled dynamic equilibrium such that co-existence results (pathogens ideally should not kill their hosts). Problems arise when pathogens jump species because the new host had not developed any resistance. These infections from related species are known as zoonoses. COVID-19 is the latest example of a virus entering another species but HIV (and various strains of influenza) were previous examples. HIV entered the human population from monkeys in Africa. These two papers outline the underlying principle of HIV and the differing epidemiologies in Africa, the USA and in Edinburgh. The underlying immunosuppression of HIV in Africa was initially hidden behind common infections and HIV first came to world awareness in focal areas of the USA as a disease seemingly limited to gay males. The epidemic of intravenous drug abuse in Edinburgh was associated with overlapping epidemics of bloodborne viruses like hepatitis B, hepatitis C and HIV.

Spatial genetic structure of 2009 H1N1 pandemic influenza established as a result of interaction with human populations in mainland China.

Identifying the spatial patterns of genetic structure of influenza A viruses is a key factor for understanding their spread and evolutionary dynamics. In this study, we used phylogenetic and Bayesian clustering analyses of genetic sequences of the A/H1N1pdm09 virus with district-level locations in mainland China to investigate the spatial genetic structure of the A/H1N1pdm09 virus across human population landscapes. Positive correlation between geographic and genetic distances indicates high degrees of genetic similarity among viruses within small geographic regions but broad-scale genetic differentiation, implying that local viral circulation was a more important driver in the formation of the spatial genetic structure of the A/H1N1pdm09 virus than even, countrywide viral mixing and gene flow. Geographic heterogeneity in the distribution of genetic subpopulations of A/H1N1pdm09 virus in mainland China indicates both local to local transmission as well as broad-range viral migration. This combination of both local and global structure suggests that both small-scale and large-scale population circulation in China is responsible for viral genetic structure. Our study provides implications for understanding the evolution and spread of A/H1N1pdm09 virus across the population landscape of mainland China, which can inform disease control strategies for future pandemics.

The coronavirus recombination pathway.

Recombination is thought to be a mechanism that facilitates cross-species transmission in coronaviruses, thus acting as a driver of coronavirus spillover and emergence. Despite its significance, the mechanism of recombination is poorly understood, limiting our potential to estimate the risk of novel recombinant coronaviruses emerging in the future. As a tool for understanding recombination, here, we outline a framework of the recombination pathway for coronaviruses. We review existing literature on coronavirus recombination, including comparisons of naturally observed recombinant genomes as well as in vitro experiments, and place the findings into the recombination pathway framework. We highlight gaps in our understanding of coronavirus recombination illustrated by the framework and outline how further experimental research is critical for disentangling the molecular mechanism of recombination from external environmental pressures. Finally, we describe how an increased understanding of the mechanism of recombination can inform pandemic predictive intelligence, with a retrospective emphasis on SARS-CoV-2.

Enhancing SARS-CoV-2 Surveillance through Regular Genomic Sequencing in Spain: The RELECOV Network.

Millions of SARS-CoV-2 whole genome sequences have been generated to date. However, good quality data and adequate surveillance systems are required to contribute to meaningful surveillance in public health. In this context, the network of Spanish laboratories for coronavirus (RELECOV) was created with the main goal of promoting actions to speed up the detection, analyses, and evaluation of SARS-CoV-2 at a national level, partially structured and financed by an ECDC-HERA-Incubator action (ECDC/GRANT/2021/024). A SARS-CoV-2 sequencing quality control assessment (QCA) was developed to evaluate the network's technical capacity. QCA full panel results showed a lower hit rate for lineage assignment compared to that obtained for variants. Genomic data comprising 48,578 viral genomes were studied and evaluated to monitor SARS-CoV-2. The developed network actions showed a 36% increase in sharing viral sequences. In addition, analysis of lineage/sublineage-defining mutations to track the virus showed characteristic mutation profiles for the Delta and Omicron variants. Further, phylogenetic analyses strongly correlated with different variant clusters, obtaining a robust reference tree. The RELECOV network has made it possible to improve and enhance the genomic surveillance of SARS-CoV-2 in Spain. It has provided and evaluated genomic tools for viral genome monitoring and characterization that make it possible to increase knowledge efficiently and quickly, promoting the genomic surveillance of SARS-CoV-2 in Spain.

Pathogenicity of GI-23 Avian Infectious Bronchitis Virus Strain Isolated in Brazil.

IBV variants belonging to the GI-23 lineage have circulated since 1998 in the Middle East and have spread to several countries over time. In Brazil, the first report of GI-23 occurred in 2022. The study aimed to evaluate the in vivo pathogenicity of exotic variant GI-23 isolates. Biological samples were screening by real-time RT-PCR and classified in to GI-1 or G1-11 lineages. Interestingly, 47.77% were not classified in these lineages. Nine of the unclassified strains were sequenced and showed a high similarity to the GI-23 strain. All nine were isolated and three, were studied for pathogenicity. At necropsy, the main observations were the presence of mucus in the trachea and congestion in the tracheal mucosa. In addition, lesions on the tracheas showed marked ciliostasis, and the ciliary activity confirmed the high pathogenicity of isolates. This variant is highly pathogenic to the upper respiratory tract and can cause severe kidney lesions. This study confirm a circulation of GI-23 strain in the country and report, to first time, the isolation of an exotic variant of IBV in Brazil.

Does Avian Coronavirus Co-Circulate with Avian Paramyxovirus and Avian Influenza Virus in Wild Ducks in Siberia?

Avian coronaviruses (ACoV) have been shown to be highly prevalent in wild bird populations. More work on avian coronavirus detection and diversity estimation is needed for the breeding territories of migrating birds, where the high diversity and high prevalence of Orthomyxoviridae and Paramyxoviridae have already been shown in wild birds. In order to detect ACoV RNA, we conducted PCR diagnostics of cloacal swab samples from birds, which we monitored during avian influenza A virus surveillance activities. Samples from two distant Asian regions of Russia (Sakhalin region and Novosibirsk region) were tested. Amplified fragments of the RNA-dependent RNA-polymerase (RdRp) of positive samples were partially sequenced to determine the species of Coronaviridae represented. The study revealed a high presence of ACoV among wild birds in Russia. Moreover, there was a high presence of birds co-infected with avian coronavirus, avian influenza virus, and avian paramyxovirus. We found one case of triple co-infection in a Northern Pintail (Anas acuta). Phylogenetic analysis revealed the circulation of a Gammacoronavirus species. A Deltacoronavirus species was not detected, which supports the data regarding the low prevalence of deltacoronaviruses among surveyed bird species.

Genetic determination of regional connectivity in modelling the spread of COVID-19 outbreak for more efficient mitigation strategies.

For the COVID-19 pandemic, viral transmission has been documented in many historical and geographical contexts. Nevertheless, few studies have explicitly modeled the spatiotemporal flow based on genetic sequences, to develop mitigation strategies. Additionally, thousands of SARS-CoV-2 genomes have been sequenced with associated records, potentially providing a rich source for such spatiotemporal analysis, an unprecedented amount during a single outbreak. Here, in a case study of seven states, we model the first wave of the outbreak by determining regional connectivity from phylogenetic sequence information (i.e. "genetic connectivity"), in addition to traditional epidemiologic and demographic parameters. Our study shows nearly all of the initial outbreak can be traced to a few lineages, rather than disconnected outbreaks, indicative of a mostly continuous initial viral flow. While the geographic distance from hotspots is initially important in the modeling, genetic connectivity becomes increasingly significant later in the first wave. Moreover, our model predicts that isolated local strategies (e.g. relying on herd immunity) can negatively impact neighboring regions, suggesting more efficient mitigation is possible with unified, cross-border interventions. Finally, our results suggest that a few targeted interventions based on connectivity can have an effect similar to that of an overall lockdown. They also suggest that while successful lockdowns are very effective in mitigating an outbreak, less disciplined lockdowns quickly decrease in effectiveness. Our study provides a framework for combining phylodynamic and computational methods to identify targeted interventions.

Respiratory syncytial virus surge in 2022 caused by lineages already present before the COVID-19 pandemic.

In 2022, Austria experienced a severe respiratory syncytial virus (RSV) epidemic with an earlier-than-usual start (Weeks 35/2021-45/2022) and increased numbers of pediatric patients in emergency departments. This surge came 2 years after a season with no cases detected as a result of coronavirus disease 2019 nonpharmaceutical interventions. We analyzed epidemiologic patterns and the phylodynamics of RSV based on approximately 30 800 respiratory specimens collected year-round over 10 years from ambulatory and hospitalized patients from 248 locations in Austria. Genomic surveillance and phylogenetic analysis of 186 RSV-A and 187 RSV-B partial glycoprotein sequences collected from 2018 to 2022 revealed that the 2022/2023 surge was driven by RSV-B in contrast to the surge in the 2021/2022 season that was driven by RSV-A. Whole-genome sequencing and phylodynamic analysis indicated that the RSV-B strain GB5.0.6a was the predominant genotype in the 2022/2023 season and emerged in late 2019. The results provide insight into RSV evolution and epidemiology that will be applicable to future monitoring efforts with the advent of novel vaccines and therapeutics.

Genetic Analysis of Dengue Virus in Severe and Non-Severe Cases in Dhaka, Bangladesh, in 2018-2022.

Dengue virus (DENV) infections have unpredictable clinical outcomes, ranging from asymptomatic or minor febrile illness to severe and fatal disease. The severity of dengue infection is at least partly related to the replacement of circulating DENV serotypes and/or genotypes. To describe clinical profiles of patients and the viral sequence diversity corresponding to non-severe and severe cases, we collected patient samples from 2018 to 2022 at Evercare Hospital Dhaka, Bangladesh. Serotyping of 495 cases and sequencing of 179 cases showed that the dominant serotype of DENV shifted from DENV2 in 2017 and 2018 to DENV3 in 2019. DENV3 persisted as the only representative serotype until 2022. Co-circulation of clades B and C of the DENV2 cosmopolitan genotype in 2017 was replaced by circulation of clade C alone in 2018 with all clones disappearing thereafter. DENV3 genotype I was first detected in 2017 and was the only genotype in circulation until 2022. We observed a high incidence of severe cases in 2019 when the DENV3 genotype I became the only virus in circulation. Phylogenetic analysis revealed clusters of severe cases in several different subclades of DENV3 genotype I. Thus, these serotype and genotype changes in DENV may explain the large dengue outbreaks and increased severity of the disease in 2019.

[Molecular epidemiological analysis of SARS-CoV-2 genovariants in Moscow and Moscow region].

INTRODUCTION: SARS-CoV-2, a severe acute respiratory illness virus that emerged in China in late 2019, continues to spread rapidly around the world, accumulating mutations and thus causing serious concern. Five virus variants of concern are currently known: Alpha (lineage B.1.1.7), Beta (lineage B.1.351), Gamma (lineage P.1), Delta (lineage B.1.617.2), and Omicron (lineage B.1.1.529). In this study, we conducted a molecular epidemiological analysis of the most prevalent genovariants in Moscow and the region. The aim of the study is to estimate the distribution of various variants of SARS-CoV-2 in Moscow city and the Moscow Region. MATERIALS AND METHODS: 227 SARS-CoV-2 sequences were used for analysis. Isolation of the SARS-CoV-2 virus was performed on Vero E6 cell culture. Sequencing was performed by the Sanger method. Bioinformatic analysis was carried out using software packages: MAFFT, IQ-TREE v1.6.12, jModelTest 2.1.7, Nextstrain, Auspice v2.34. RESULTS: As a result of phylogenetic analysis, we have identified the main variants of the virus circulating in Russia that have been of concern throughout the existence of the pandemic, namely: variant B.1.1.7, which accounted for 30% (9/30), AY.122, which accounted for 16.7% (5/30), BA.1.1 with 20% (6/30) and B.1.1 with 33.3% (10/30). When examining Moscow samples for the presence of mutations in SARS-CoV-2 structural proteins of different genovariants, a significant percentage of the most common substitutions was recorded: S protein D614G (86.7%), P681H/R (63.3%), E protein T9I (20.0%); M protein I82T (30.0%), D3G (20.0%), Q19E (20.0%) and finally N protein R203K/M (90.0%), G204R/P (73.3 %). CONCLUSION: The study of the frequency and impact of mutations, as well as the analysis of the predominant variants of the virus are important for the development and improvement of vaccines for the prevention of COVID-19. Therefore, ongoing molecular epidemiological studies are needed, as these data provide important information about changes in the genome of circulating SARS-CoV-2 variants.

A tale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India.

BACKGROUND: Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data. METHODS: A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a "band of five" outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5). RESULTS: The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM. CONCLUSIONS: The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implications for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.

Risk factors for infection with influenza A(H3N2) virus on a US university campus, October-November 2021.

BACKGROUND: Knowledge of the specific dynamics of influenza introduction and spread in university settings is limited. METHODS: Persons with acute respiratory illness symptoms received influenza testing by molecular assay during October 6-November 23, 2022. Viral sequencing and phylogenetic analysis were conducted on nasal swab samples from case-patients. Case-control analysis of a voluntary survey of persons tested was used to identify factors associated with influenza; logistic regression was conducted to calculate odds ratios and 95% CIs. A subset of case-patients tested during the first month of the outbreak was interviewed to identify sources of introduction and early spread. RESULTS: Among 3268 persons tested, 788 (24.1%) tested positive for influenza; 744 (22.8%) were included in the survey analysis. All 380 sequenced specimens were influenza A (H3N2) virus clade 3C.2a1b.2a.2, suggesting rapid transmission. Influenza (OR [95% CI]) was associated with indoor congregate dining (1.43 [1.002-2.03]), attending large gatherings indoors (1.83 [1.26-2.66]) or outdoors (2.33 [1.64-3.31]), and varied by residence type (apartment with ≥1 roommate: 2.93 [1.21-7.11], residence hall room alone: 4.18 [1.31-13.31], or with roommate: 6.09 [2.46-15.06], or fraternity/sorority house: 15.13 [4.30-53.21], all compared with single-dwelling apartment). Odds of influenza were lower among persons who left campus for ≥1 day during the week before their influenza test (0.49 [0.32-0.75]). Almost all early cases reported attending large events. CONCLUSIONS: Congregate living and activity settings on university campuses can lead to rapid spread of influenza following introduction. Isolating following a positive influenza test or administering antiviral medications to exposed persons may help mitigate outbreaks.

Using machine learning to detect coronaviruses potentially infectious to humans.

Establishing the host range for novel viruses remains a challenge. Here, we address the challenge of identifying non-human animal coronaviruses that may infect humans by creating an artificial neural network model that learns from spike protein sequences of alpha and beta coronaviruses and their binding annotation to their host receptor. The proposed method produces a human-Binding Potential (h-BiP) score that distinguishes, with high accuracy, the binding potential among coronaviruses. Three viruses, previously unknown to bind human receptors, were identified: Bat coronavirus BtCoV/133/2005 and Pipistrellus abramus bat coronavirus HKU5-related (both MERS related viruses), and Rhinolophus affinis coronavirus isolate LYRa3 (a SARS related virus). We further analyze the binding properties of BtCoV/133/2005 and LYRa3 using molecular dynamics. To test whether this model can be used for surveillance of novel coronaviruses, we re-trained the model on a set that excludes SARS-CoV-2 and all viral sequences released after the SARS-CoV-2 was published. The results predict the binding of SARS-CoV-2 with a human receptor, indicating that machine learning methods are an excellent tool for the prediction of host expansion events.

[Genetic diversity of Siberian bovine coronavirus isolates (Coronaviridae: Coronavirinae: Betacoronavirus-1: Bovine-Like coronaviruses)].

INTRODUCTION: Bovine coronaviruses (BCoVs) are causative agents of diarrhea, respiratory diseases in calves and winter cow dysentery. The study of genetic diversity of these viruses is topical issue. The purpose of the research is studying the genetic diversity of BCoV isolates circulating among dairy cattle in Siberia. MATERIALS AND METHODS: Specimens used in this study were collected from animals that died or was forcedly slaughtered before the start of the study. The target for amplification were nucleotide sequences of S and N gene regions. RESULTS: Based on the results of RT-PCR testing, virus genome was present in 16.3% of samples from calves with diarrheal syndrome and in 9.9% with respiratory syndrome. The nucleotide sequences of S gene region were determined for 18 isolates, and N gene sequences - for 12 isolates. Based on S gene, isolates were divided into two clades each containing two subclades. First subclade of first clade (European line) included 11 isolates. Second one included classic strains Quebec and Mebus, strains from Europe, USA and Korea, but none of sequences from this study belonged to this subclade. 6 isolates belonged to first subclade of second clade (American-Asian line). Second subclade (mixed line) included one isolate. N gene sequences formed two clades, one of them included two subclades. First subclade included 3 isolates (American-Asian line), and second subclade (mixed) included one isolate. Second clade (mixed) included 8 sequences. No differences in phylogenetic grouping between intestinal and respiratory isolates, as well as according to their geographic origin were identified. CONCLUSION: The studied population of BCoV isolates is heterogeneous. Nucleotide sequence analysis is a useful tool for studying molecular epidemiology of BCoV. It can be beneficial for choice of vaccines to be used in a particular geographic region.

Distinct Red Blotch Disease Epidemiological Dynamics in Two Nearby Vineyards.

Grapevine red blotch virus (GRBV) causes red blotch disease and is transmitted by the three-cornered alfalfa hopper, Spissistilus festinus. GRBV isolates belong to a minor phylogenetic clade 1 and a predominant clade 2. Spatiotemporal disease dynamics were monitored in a 1-hectare 'Merlot' vineyard planted in California in 2015. Annual surveys first revealed disease onset in 2018 and a 1.6% disease incidence in 2022. Ordinary runs and phylogenetic analyses documented significant aggregation of vines infected with GRBV clade 1 isolates in one corner of the vineyard (Z = -4.99), despite being surrounded by clade 2 isolates. This aggregation of vines harboring isolates from a non-prevalent clade is likely due to infected rootstock material at planting. GRBV clade 1 isolates were predominant in 2018-2019 but displaced by clade 2 isolates in 2021-2022, suggesting an influx of the latter isolates from outside sources. This study is the first report of red blotch disease progress immediately after vineyard establishment. A nearby 1.5-hectare 'Cabernet Sauvignon' vineyard planted in 2008 with clone 4 (CS4) and 169 (CS169) vines was also surveyed. Most CS4 vines that exhibited disease symptoms one-year post-planting, likely due to infected scion material, were aggregated (Z = -1.73). GRBV isolates of both clades were found in the CS4 vines. Disease incidence was only 1.4% in non-infected CS169 vines in 2022 with sporadic infections of isolates from both clades occurring via secondary spread. Through disentangling GRBV infections due to the planting material and S. festinus-mediated transmission, this study illustrated how the primary virus source influences epidemiological dynamics of red blotch disease.

Decoding the Fundamental Drivers of Phylodynamic Inference.

Despite its increasing role in the understanding of infectious disease transmission at the applied and theoretical levels, phylodynamics lacks a well-defined notion of ideal data and optimal sampling. We introduce a method to visualize and quantify the relative impact of pathogen genome sequence and sampling times-two fundamental sources of data for phylodynamics under birth-death-sampling models-to understand how each drives phylodynamic inference. Applying our method to simulated data and real-world SARS-CoV-2 and H1N1 Influenza data, we use this insight to elucidate fundamental trade-offs and guidelines for phylodynamic analyses to draw the most from sequence data. Phylodynamics promises to be a staple of future responses to infectious disease threats globally. Continuing research into the inherent requirements and trade-offs of phylodynamic data and inference will help ensure phylodynamic tools are wielded in ever more targeted and efficient ways.

Identification of Evolutionary Trajectories Shared across Human Betacoronaviruses.

Comparing the evolution of distantly related viruses can provide insights into common adaptive processes related to shared ecological niches. Phylogenetic approaches, coupled with other molecular evolution tools, can help identify mutations informative on adaptation, although the structural contextualization of these to functional sites of proteins may help gain insight into their biological properties. Two zoonotic betacoronaviruses capable of sustained human-to-human transmission have caused pandemics in recent times (SARS-CoV-1 and SARS-CoV-2), although a third virus (MERS-CoV) is responsible for sporadic outbreaks linked to animal infections. Moreover, two other betacoronaviruses have circulated endemically in humans for decades (HKU1 and OC43). To search for evidence of adaptive convergence between established and emerging betacoronaviruses capable of sustained human-to-human transmission (HKU1, OC43, SARS-CoV-1, and SARS-CoV-2), we developed a methodological pipeline to classify shared nonsynonymous mutations as putatively denoting homoplasy (repeated mutations that do not share direct common ancestry) or stepwise evolution (sequential mutations leading towards a novel genotype). In parallel, we look for evidence of positive selection and draw upon protein structure data to identify potential biological implications. We find 30 candidate mutations, from which 4 (codon sites 18121 [nsp14/residue 28], 21623 [spike/21], 21635 [spike/25], and 23948 [spike/796]; SARS-CoV-2 genome numbering) further display evolution under positive selection and proximity to functional protein regions. Our findings shed light on potential mechanisms underlying betacoronavirus adaptation to the human host and pinpoint common mutational pathways that may occur during establishment of human endemicity.

Molecular transition of SARS-CoV-2 from critical patients during the first year of the COVID-19 pandemic in Mexico City.

Background: The SARS-CoV-2 virus has caused unprecedented mortality since its emergence in late 2019. The continuous evolution of the viral genome through the concerted action of mutational forces has produced distinct variants that became dominant, challenging human immunity and vaccine development. Aim and methods: In this work, through an integrative genomic approach, we describe the molecular transition of SARS-CoV-2 by analyzing the viral whole genome sequences from 50 critical COVID-19 patients recruited during the first year of the pandemic in Mexico City. Results: Our results revealed differential levels of the evolutionary forces across the genome and specific mutational processes that have shaped the first two epidemiological waves of the pandemic in Mexico. Through phylogenetic analyses, we observed a genomic transition in the circulating SARS-CoV-2 genomes from several lineages prevalent in the first wave to a dominance of the B.1.1.519 variant (defined by T478K, P681H, and T732A mutations in the spike protein) in the second wave. Conclusion: This work contributes to a better understanding of the evolutionary dynamics and selective pressures that act at the genomic level, the prediction of more accurate variants of clinical significance, and a better comprehension of the molecular mechanisms driving the evolution of SARS-CoV-2 to improve vaccine and drug development.

Coronavirus sampling and surveillance in bats from 1996-2019: a systematic review and meta-analysis.

The emergence of SARS-CoV-2 highlights a need for evidence-based strategies to monitor bat viruses. We performed a systematic review of coronavirus sampling (testing for RNA positivity) in bats globally. We identified 110 studies published between 2005 and 2020 that collectively reported positivity from 89,752 bat samples. We compiled 2,274 records of infection prevalence at the finest methodological, spatiotemporal and phylogenetic level of detail possible from public records into an open, static database named datacov, together with metadata on sampling and diagnostic methods. We found substantial heterogeneity in viral prevalence across studies, reflecting spatiotemporal variation in viral dynamics and methodological differences. Meta-analysis identified sample type and sampling design as the best predictors of prevalence, with virus detection maximized in rectal and faecal samples and by repeat sampling of the same site. Fewer than one in five studies collected and reported longitudinal data, and euthanasia did not improve virus detection. We show that bat sampling before the SARS-CoV-2 pandemic was concentrated in China, with research gaps in South Asia, the Americas and sub-Saharan Africa, and in subfamilies of phyllostomid bats. We propose that surveillance strategies should address these gaps to improve global health security and enable the origins of zoonotic coronaviruses to be identified.

A Candidate Antigen of the Recombinant Membrane Protein Derived from the Porcine Deltacoronavirus Synthetic Gene to Detect Seropositive Pigs.

Porcine deltacoronavirus (PDCoV) is an emergent swine coronavirus which infects cells from the small intestine and induces watery diarrhea, vomiting and dehydration, causing mortality in piglets (>40%). The aim of this study was to evaluate the antigenicity and immunogenicity of the recombinant membrane protein (M) of PDCoV (rM-PDCoV), which was developed from a synthetic gene obtained after an in silico analysis with a group of 138 GenBank sequences. A 3D model and phylogenetic analysis confirmed the highly conserved M protein structure. Therefore, the synthetic gene was successfully cloned in a pETSUMO vector and transformed in E. coli BL21 (DE3). The rM-PDCoV was confirmed by SDS-PAGE and Western blot with ~37.7 kDa. The rM-PDCoV immunogenicity was evaluated in immunized (BLAB/c) mice and iELISA. The data showed increased antibodies from 7 days until 28 days (p < 0.001). The rM-PDCoV antigenicity was analyzed using pig sera samples from three states located in "El Bajío" Mexico and positive sera were determined. Our results show that PDCoV has continued circulating on pig farms in Mexico since the first report in 2019; therefore, the impact of PDCoV on the swine industry could be higher than reported in other studies.