StrainHub: a phylogenetic tool to construct pathogen transmission networks

Epidemiological Characterization and Genetic Variation of the SARS-CoV-2 Delta Variant in Palestine

The emergence of new SARS-CoV-2 variants in Palestine highlights the need for continuous genetic surveillance and accurate screening strategies. This case series study aimed to investigate the geographic distribution and genetic variation of the SARS-CoV-2 Delta Variant in Palestine in August 2021. Samples were collected at random in August 2021 (n = 571) from eight districts in the West Bank, Palestine. All samples were confirmed as positive for COVID-19 by RT-PCR. The samples passed the quality control test and were successfully sequenced using the ARTIC protocol. The Delta Variant was revealed to have four dominant lineages: B.1.617 (19%), AY.122 (18%), AY.106 (17%), and AY.121 (13%). The study revealed eight significant purely spatial clusters (p < 0.005) distributed in the northern and southern parts of Palestine. Phylogenetic analysis of SARS-CoV-2 genomes (n = 552) showed no geographically specific clades. The haplotype network revealed three haplogroups without any geographic distribution. Chronologically, the Delta Variant peak in Palestine was shortly preceded by the one in the neighboring Israeli community and shortly followed by the peak in Jordan. In addition, the study revealed an extremely intense transmission network of the Delta Variant circulating between the Palestinian districts as hubs (SHR ≈ 0.5), with Al-Khalil, the district with the highest prevalence of COVID-19, witnessing the highest frequency of transitions. Genetic diversity analysis indicated closely related haplogroups, as haplotype diversity (Hd) is high but has low nucleotide diversity (π). However, nucleotide diversity (π) in Palestine is still higher than the global figures. Neutrality tests were significantly (p < 0.05) low, including Tajima's D, Fu-Li's F, and Fu-Li's D, suggesting one or more of the following: population expansion, selective sweep, and natural negative selection. Wright's F-statistic (Fst) showed genetic differentiation (Fst > 0.25) with low to medium gene flow (Nm). Recombination events were minimal between clusters (Rm) and between adjacent sites (Rs). The study confirms the utility of the whole genome sequence as a surveillance system to track the emergence of new SARS-CoV-2 variants for any possible geographical association and the use of genetic variation analysis and haplotype networking to delineate any minimal change or slight deviation in the viral genome from a reference strain.

Optimizing ancestral trait reconstruction of large HIV Subtype C datasets through multiple-trait subsampling

Large datasets along with sampling bias represent a challenge for phylodynamic reconstructions, particularly when the study data are obtained from various heterogeneous sources and/or through convenience sampling. In this study, we evaluate the presence of unbalanced sampled distribution by collection date, location, and risk group of human immunodeficiency virus Type 1 Subtype C using a comprehensive subsampling strategy and assess their impact on the reconstruction of the viral spatial and risk group dynamics using phylogenetic comparative methods. Our study shows that a most suitable dataset for ancestral trait reconstruction can be obtained through subsampling by all available traits, particularly using multigene datasets. We also demonstrate that sampling bias is inflated when considerable information for a given trait is unavailable or of poor quality, as we observed for the trait risk group. In conclusion, we suggest that, even if traits are not well recorded, including them deliberately optimizes the representativeness of the original dataset rather than completely excluding them. Therefore, we advise the inclusion of as many traits as possible with the aid of subsampling approaches in order to optimize the dataset for phylodynamic analysis while reducing the computational burden. This will benefit research communities investigating the evolutionary and spatio-temporal patterns of infectious diseases.

Genome-wide study of globally distributed respiratory syncytial virus (RSV) strains implicates diversification utilizing phylodynamics and mutational analysis

Respiratory syncytial virus (RSV) is a common respiratory pathogen that causes mild cold-like symptoms and severe lower respiratory tract infections, causing hospitalizations in children, the elderly and immunocompromised individuals. Due to genetic variability, this virus causes life-threatening pneumonia and bronchiolitis in young infants. Thus, we examined 3600 whole genome sequences submitted to GISAID by 31 December 2022 to examine the genetic variability of RSV. While RSVA and RSVB coexist throughout RSV seasons, RSVA is more prevalent, fatal, and epidemic-prone in several countries, including the United States, the United Kingdom, Australia, and China. Additionally, the virus's attachment glycoprotein and fusion protein were highly mutated, with RSVA having higher Shannon entropy than RSVB. The genetic makeup of these viruses contributes significantly to their prevalence and epidemic potential. Several strain-specific SNPs co-occurred with specific haplotypes of RSVA and RSVB, followed by different haplotypes of the viruses. RSVA and RSVB have the highest linkage probability at loci T12844A/T3483C and G13959T/C2198T, respectively. The results indicate that specific haplotypes and SNPs may significantly affect their spread. Overall, this analysis presents a promising strategy for tracking the evolving epidemic situation and genetic variants of RSV, which could aid in developing effective control, prophylactic, and treatment strategies.

Increased interregional virus exchange and nucleotide diversity outline the expansion of chikungunya virus in Brazil

The emergence and reemergence of mosquito-borne diseases in Brazil such as yellow fever, zika, chikungunya, and dengue have had serious impacts on public health. Concerns have been raised due to the rapid dissemination of the chikungunya virus across the country since its first detection in 2014 in Northeast Brazil. In this work, we carried out on-site training activities in genomic surveillance in partnership with the National Network of Public Health Laboratories that have led to the generation of 422 chikungunya virus genomes from 12 Brazilian states over the past two years (2021-2022), a period that has seen more than 312 thousand chikungunya fever cases reported in the country. These genomes increased the amount of available data and allowed a more comprehensive characterization of the dispersal dynamics of the chikungunya virus East-Central-South-African lineage in Brazil. Tree branching patterns revealed the emergence and expansion of two distinct subclades. Phylogeographic analysis indicated that the northeast region has been the leading hub of virus spread towards other regions. Increased frequency of C > T transitions among the new genomes suggested that host restriction factors from the immune system such as ADAR and AID/APOBEC deaminases might be driving the genetic diversity of the chikungunya virus in Brazil.

Phylogeny, ancestral ranges and reclassification of sand dollars

Classification of the Class Echinoidea is under significant revision in light of emerging molecular phylogenetic evidence. In particular, the sister-group relationships within the superorder Luminacea (Echinoidea: Irregularia) have been considerably updated. However, the placement of many families remains largely unresolved due to a series of incongruent evidence obtained from morphological, paleontological, and genetic data for the majority of extant representatives. In this study, we investigated the phylogenetic relationships of 25 taxa, belonging to eleven luminacean families. We proposed three new superfamilies: Astriclypeoidea, Mellitoidea, and Taiwanasteroidea (including Dendrasteridae, Taiwanasteridae, Scutellidae, and Echinarachniidae), instead of the currently recognized superfamily Scutelloidea Gray, 1825. In light of the new data obtained from ten additional species, the historical biogeography reconstructed shows that the tropical western Pacific and eastern Indian Oceans are the cradle for early sand dollar diversification. Hothouse conditions during the late Cretaceous and early Paleogene were coupled with diversification events of major clades of sand dollars. We also demonstrate that Taiwan fauna can play a key role in terms of understanding the major Cenozoic migration and dispersal events in the evolutionary history of Luminacea.

Increased interregional virus exchange and nucleotide diversity outline the expansion of the chikungunya virus ECSA lineage in Brazil

The emergence and reemergence of mosquito-borne diseases in Brazil such as Yellow Fever, Zika, Chikungunya, and Dengue have had serious impacts on public health. Concerns have been raised due to the rapid dissemination of the chikungunya virus (CHIKV) across the country since its first detection in 2014 in Northeast Brazil. Faced with this scenario, on-site training activities in genomic surveillance carried out in partnership with the National Network of Public Health Laboratories have led to the generation of 422 CHIKV genomes from 12 Brazilian states over the past two years (2021-2022), a period that has seen more than 312 thousand chikungunya fever cases reported in the country. These new genomes increased the amount of available data and allowed a more comprehensive characterization of the dispersion dynamics of the CHIKV East-Central-South-African (ECSA) lineage in Brazil. Tree branching patterns revealed the emergence and expansion of two distinct subclades. Phylogeographic analysis indicated that the northeast region has been the leading hub of virus spread towards other regions. Increased frequency of C>T transitions among the new genomes suggested that host restriction factors from the immune system such as ADAR and AID/APOBEC deaminases might be driving CHIKV ECSA lineage genetic diversity in Brazil.

SOPHIE: Viral outbreak investigation and transmission history reconstruction in a joint phylogenetic and network theory framework

Genomic epidemiology is now widely used for viral outbreak investigations. Still, this methodology faces many challenges. First, few methods account for intra-host viral diversity. Second, maximum parsimony principle continues to be employed for phylogenetic inference of transmission histories, even though maximum likelihood or Bayesian models are usually more consistent. Third, many methods utilize case-specific data, such as sampling times or infection exposure intervals. This impedes study of persistent infections in vulnerable groups, where such information has a limited use. Finally, most methods implicitly assume that transmission events are independent, although common source outbreaks violate this assumption. We propose a maximum likelihood framework, SOPHIE, based on the integration of phylogenetic and random graph models. It infers transmission networks from viral phylogenies and expected properties of inter-host social networks modeled as random graphs with given expected degree distributions. SOPHIE is scalable, accounts for intra-host diversity, and accurately infers transmissions without case-specific epidemiological data.

Genomic surveillance unfolds the SARS-CoV-2 transmission and divergence dynamics in Bangladesh

The highly pathogenic virus SARS-CoV-2 has shattered the healthcare system of the world causing the COVID-19 pandemic since first detected in Wuhan, China. Therefore, scrutinizing the genome structure and tracing the transmission of the virus has gained enormous interest in designing appropriate intervention strategies to control the pandemic. In this report, we examined 4,622 sequences from Bangladesh and found that they belonged to thirty-five major PANGO lineages, while Delta alone accounted for 39%, and 78% were from just four primary lineages. Our research has also shown Dhaka to be the hub of viral transmission and observed the virus spreading back and forth across the country at different times by building a transmission network. The analysis resulted in 7,659 unique mutations, with an average of 24.61 missense mutations per sequence. Moreover, our analysis of genetic diversity and mutation patterns revealed that eight genes were under negative selection pressure to purify deleterious mutations, while three genes were under positive selection pressure. Together with an ongoing genomic surveillance program, these data will contribute to a better understanding of SARS-CoV-2, as well as its evolution pattern and pandemic characteristics in Bangladesh.

Identifying SARS-CoV-2 regional introductions and transmission clusters in real time

The unprecedented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) global sequencing effort has suffered from an analytical bottleneck. Many existing methods for phylogenetic analysis are designed for sparse, static datasets and are too computationally expensive to apply to densely sampled, rapidly expanding datasets when results are needed immediately to inform public health action. For example, public health is often concerned with identifying clusters of closely related samples, but the sheer scale of the data prevents manual inspection and the current computational models are often too expensive in time and resources. Even when results are available, intuitive data exploration tools are of critical importance to effective public health interpretation and action. To help address this need, we present a phylogenetic heuristic that quickly and efficiently identifies newly introduced strains in a region, resulting in clusters of infected individuals, and their putative geographic origins. We show that this approach performs well on simulated data and yields results largely congruent with more sophisticated Bayesian phylogeographic modeling approaches. We also introduce Cluster-Tracker (https://clustertracker.gi.ucsc.edu/), a novel interactive web-based tool to facilitate effective and intuitive SARS-CoV-2 geographic data exploration and visualization across the USA. Cluster-Tracker is updated daily and automatically identifies and highlights groups of closely related SARS-CoV-2 infections resulting from the transmission of the virus between two geographic areas by travelers, streamlining public health tracking of local viral diversity and emerging infection clusters. The site is open-source and designed to be easily configured to analyze any chosen region, making it a useful resource globally. The combination of these open-source tools will empower detailed investigations of the geographic origins and spread of SARS-CoV-2 and other densely sampled pathogens.

Gene Polymorphisms Among Plasmodium vivax Geographical Isolates and the Potential as New Biomarkers for Gametocyte Detection

The unique biological features of Plasmodium vivax not only make it difficult to control but also to eliminate. For the transmission of the malaria parasite from infected human to the vector, gametocytes play a major role. The transmission potential of a malarial infection is inferred based on microscopic detection of gametocytes and molecular screening of genes in the female gametocytes. Microscopy-based detection methods could grossly underestimate the reservoirs of infection as gametocytes may occur as submicroscopic or as micro- or macro-gametocytes. The identification of genes that are highly expressed and polymorphic in male and female gametocytes is critical for monitoring changes not only in their relative proportions but also the composition of gametocyte clones contributing to transmission over time. Recent transcriptomic study revealed two distinct clusters of highly correlated genes expressed in the P. vivax gametocytes, indicating that the male and female terminal gametocytogeneses are independently regulated. However, the detective power of these genes is unclear. In this study, we compared genetic variations of 15 and 11 genes expressed, respectively, in the female and male gametocytes among P. vivax isolates from Southeast Asia, Africa, and South America. Further, we constructed phylogenetic trees to determine the resolution power and clustering patterns of gametocyte clones. As expected, Pvs25 (PVP01_0616100) and Pvs16 (PVP01_0305600) expressed in the female gametocytes were highly conserved in all geographical isolates. In contrast, genes including 6-cysteine protein Pvs230 (PVP01_0415800) and upregulated in late gametocytes ULG8 (PVP01_1452800) expressed in the female gametocytes, as well as two CPW-WPC family proteins (PVP01_1215900 and PVP01_1320100) expressed in the male gametocytes indicated considerably high nucleotide and haplotype diversity among isolates. Parasite samples expressed in male and female gametocyte genes were observed in separate phylogenetic clusters and likely represented distinct gametocyte clones. Compared to Pvs25, Pvs230 (PVP01_0415800) and a CPW-WPC family protein (PVP01_0904300) showed higher expression in a subset of Ethiopian P. vivax samples. Thus, Pvs230, ULG8, and CPW-WPC family proteins including PVP01_0904300, PVP01_1215900, and PVP01_1320100 could potentially be used as novel biomarkers for detecting both sexes of P. vivax gametocytes in low-density infections and estimating transmission reservoirs.

Emergence of Two Distinct SARS-CoV-2 Gamma Variants and the Rapid Spread of P.1-like-II SARS-CoV-2 during the Second Wave of COVID-19 in Santa Catarina, Southern Brazil

The western mesoregion of the state of Santa Catarina (SC), Southern Brazil, was heavily affected as a whole by the COVID-19 pandemic in early 2021. This study aimed to evaluate the dynamics of the SARS-CoV-2 virus spreading patterns in the SC state from March 2020 to April 2021 using genomic surveillance. During this period, there were 23 distinct variants, including Beta and Gamma, among which the Gamma and related lineages were predominant in the second pandemic wave within SC. A regionalization of P.1-like-II in the Western SC region was observed, concomitant to the increase in cases, mortality, and the case fatality rate (CFR) index. This is the first evidence of the regionalization of the SARS-CoV-2 transmission in SC and it highlights the importance of tracking the variants, dispersion, and impact of SARS-CoV-2 on the public health systems.

Evidence for common ancestry and microevolution of passerine-adapted Salmonella enterica serovar Typhimurium in the UK and USA

The evolution of Salmonella enterica serovar Typhimurium (S. Typhimurium) within passerines has resulted in pathoadaptation of this serovar to the avian host in Europe. Recently, we identified an S. Typhimurium lineage from passerines in North America. The emergence of passerine-adapted S. Typhimurium in Europe and North America raises questions regarding its evolutionary origin. Here, we demonstrated that the UK and US passerine-adapted S. Typhimurium shared a common ancestor from ca. 1838, and larids played a key role in the clonal expansion by disseminating the common ancestor between North America and Europe. Further, we identified virulence gene signatures common in the passerine- and larid-adapted S. Typhimurium, including conserved pseudogenes in fimbrial gene lpfD and Type 3 Secretion System (T3SS) effector gene steC. However, the UK and US passerine-adapted S. Typhimurium also possessed unique virulence gene signatures (i.e. pseudogenes in fimbrial gene fimC and T3SS effector genes sspH2, gogB, sseJ and sseK2), and the majority of them (38/47) lost a virulence plasmid pSLT that was present in the larid-adapted S. Typhimurium. These results provide evidence that passerine-adapted S. Typhimurium share a common ancestor with those from larids, and the divergence of passerine- and larid-adapted S. Typhimurium might be due to pseudogenization or loss of specific virulence genes.

Methods Combining Genomic and Epidemiological Data in the Reconstruction of Transmission Trees: A Systematic Review

In order to better understand transmission dynamics and appropriately target control and preventive measures, studies have aimed to identify who-infected-whom in actual outbreaks. Numerous reconstruction methods exist, each with their own assumptions, types of data, and inference strategy. Thus, selecting a method can be difficult. Following PRISMA guidelines, we systematically reviewed the literature for methods combing epidemiological and genomic data in transmission tree reconstruction. We identified 22 methods from the 41 selected articles. We defined three families according to how genomic data was handled: a non-phylogenetic family, a sequential phylogenetic family, and a simultaneous phylogenetic family. We discussed methods according to the data needed as well as the underlying sequence mutation, within-host evolution, transmission, and case observation. In the non-phylogenetic family consisting of eight methods, pairwise genetic distances were estimated. In the phylogenetic families, transmission trees were inferred from phylogenetic trees either simultaneously (nine methods) or sequentially (five methods). While a majority of methods (17/22) modeled the transmission process, few (8/22) took into account imperfect case detection. Within-host evolution was generally (7/8) modeled as a coalescent process. These practical and theoretical considerations were highlighted in order to help select the appropriate method for an outbreak.

Genomic epidemiology of Salmonella enterica circulating in surface waters used in agriculture and aquaculture in central Mexico

Salmonella enterica can survive in surface waters (SuWa), and the role of nonhost environments in its transmission has acquired increasing relevance. In this study, we conducted comparative genomic analyses of 172 S. enterica isolates collected from SuWa across 3 months in six states of central Mexico during 2019. S. enterica transmission dynamics were assessed using 87 experimental and 112 public isolates from Mexico collected during 2002 through 2019. We also studied genetic relatedness between SuWa isolates and human clinical strains collected in North America during 2005 through 2020. Among experimental isolates, we identified 41 S. enterica serovars and 56 multilocus sequence types (STs). Predominant serovars were Senftenberg (n = 13), Meleagridis, Agona, and Newport (n = 12 each), Give (n = 10), Anatum (n = 8), Adelaide (n = 7), and Infantis, Mbandaka, Ohio, and Typhimurium (n = 6 each). We observed a high genetic diversity in the sample under study, as well as clonal dissemination of strains across distant regions. Some of these strains are epidemiologically important (ST14, ST45, ST118, ST132, ST198, and ST213) and were genotypically close to those involved in clinical cases in North America. Transmission network analysis suggests that SuWa are a relevant source of S. enterica (0.7 source/hub ratio) and contribute to its dissemination as isolates from varied sources and clinical cases have SuWa isolates as common ancestors. Overall, the study shows that SuWa act as reservoirs of various S. enterica serovars of public health significance. Further research is needed to better understand the mechanisms involved in SuWa contamination by S. enterica, as well as to develop interventions to contain its dissemination in food production settings.

IMPORTANCE Surface waters are heavily used in food production worldwide. Several human pathogens can survive in these waters for long periods and disseminate to food production environments, contaminating our food supply. One of these pathogens is Salmonella enterica, a leading cause of foodborne infections, hospitalizations, and deaths in many countries. This research demonstrates the role of surface waters as a vehicle for the transmission of Salmonella along food production chains. It also shows that some strains circulating in surface waters are very similar to those implicated in human infections and harbor genes that confer resistance to multiple antibiotics, posing a risk to public health. This study contributes to expand our current knowledge on the ecology and epidemiology of Salmonella in surface waters.

Plasmodium vivax From Duffy-Negative and Duffy-Positive Individuals Share Similar Gene Pools in East Africa

Plasmodium vivax malaria was thought to be rare in Africa, but an increasing number of P. vivax cases reported across Africa and in Duffy-negative individuals challenges this dogma. The genetic characteristics of P. vivax in Duffy-negative infections, the transmission of P. vivax in East Africa, and the impact of environments on transmission remain largely unknown. This study examined genetic and transmission features of P. vivax from 107 Duffy-negative and 305 Duffy-positive individuals in Ethiopia and Sudan. No clear genetic differentiation was found in P. vivax between the 2 Duffy groups, indicating between-host transmission. P. vivax from Ethiopia and Sudan showed similar genetic clusters, except samples from Khartoum, possibly due to distance and road density that inhibited parasite gene flow. This study is the first to show that P. vivax can transmit to and from Duffy-negative individuals and provides critical insights into the spread of P. vivax in sub-Saharan Africa.

Prevalence of resistance-associated substitutions and phylogenetic analysis of hepatitis C virus infection in Russia

OBJECTIVES

Due to limited hepatitis C virus (HCV) sequence availability from patients in Russia, the relationship between subtypes and baseline resistance-associated substitutions (RAS) to direct antiretroviral treatment outcome is not fully understood.

METHODS

Deep sequencing of HCV NS3, NS5A, and NS5B sequences was performed on plasma HCV samples from 412 direct-acting antiviral (DAA)-naïve patients from Russia. Phylogenetic analysis was performed to investigate sequence similarities between HCV strains from Russia, Asia, Europe, and North America. Pretreatment HCV RAS was assessed with a 15% cutoff.

RESULTS

HCV genotype GT1b and GT3a sequences in Russia were related to strains in Europe and Asia. The prevalence of GT1a and GT2a was low in Russia. In GT1b, the prevalence of NS5A Y93H was lower in Russia (6%) compared with Asia (15%). The prevalence of NS5B L159F was similar between Russia and Europe (26-39%). GT3a RAS prevalence was similar between Russia and Asia, Europe, and North America. The 2k/1b recombinant strain in Russia was related to strains from Europe. A higher prevalence of the NS5A RAS L31M (10%) was observed in 2k/1b sequences compared to GT1b (1-6%).

CONCLUSIONS

The prevalence of RASs and the phylogenetic analysis showed similarities in HCV strains between Russia, Europe, and North America. This information may be useful for HCV regimens in Russia.

Evolutionary history of H5 highly pathogenic avian influenza viruses (clade 2.3.4.4c) circulating in Taiwan during 2015-2018

The highly pathogenic avian influenza (HPAI) virus A/goose/Guangdong/1/96 H5N1 (Gs/GD) lineage has been transmitted globally and has caused deaths in wild birds, poultry, and humans. Clade 2.3.4.4c, one of the subclades of the Gs/GD lineage, spread through Taiwan in late 2014 and become an endemic virus. We analyzed 239 newly sequenced HPAI clade H5Nx isolates to explore the phylogenetic relationships, divergence times, and evolutionary history of Taiwan HPAI H5Nx viruses from 2015 to 2018. Overall, 15 reassortant genotypes were identified among H5N2, H5N3, and H5N8 viruses. Maximum likelihood and Bayesian phylogenies based on homologous hemagglutinin (HA) and matrix protein (MP) genes suggest that Taiwan HPAI H5Nx viruses share a most recent common ancestor that has diversified since October 2014 and is closely related to two HPAI H5N8 viruses identified from wild birds in Japan. Two waves of HPAI caused by multiple reassortants were identified, the first occurring in late 2014 and the second beginning in late 2016. The first wave consisted of seven H5Nx reassortants that spread through Taiwan. In the second wave, eight novel reassortants were detected which had newly introduced internal genes, mostly derived from the avian influenza virus gene pool maintained in wild birds in Asia. Phylodynamic reconstruction using the Bayesian Skygrid model revealed varied fluctuating patterns of relative genetic diversity among reassortants. The mean evolutionary rate also varied among reassortants and subtypes. The neuraminidase (NA) gene evolved faster than the HA gene in H5N2 viruses, while HA evolved faster than NA in H5N8 viruses. The HA mean evolutionary rate ranged from 6.10 × 10^-3 to 7.73 × 10^-3 and from 5.81 × 10^-3 to 9.45 × 10^-3 substitutions/site/year for H5N2 and H5N8 viruses, respectively. The continuous circulation of HPAI H5Nx variants and the emergence of novel reassortants in Taiwan highlight that the surveillance, biosecurity, and management systems of poultry farms need to be improved and carefully executed.

Dynamic Molecular Epidemiology Reveals Lineage-Associated Single-Nucleotide Variants That Alter RNA Structure in Chikungunya Virus

Chikungunya virus (CHIKV) is an emerging Alphavirus which causes millions of human infections every year. Outbreaks have been reported in Africa and Asia since the early 1950s, from three CHIKV lineages: West African, East Central South African, and Asian Urban. As new outbreaks occurred in the Americas, individual strains from the known lineages have evolved, creating new monophyletic groups that generated novel geographic-based lineages. Building on a recently updated phylogeny of CHIKV, we report here the availability of an interactive CHIKV phylodynamics dataset, which is based on more than 900 publicly available CHIKV genomes. We provide an interactive view of CHIKV molecular epidemiology built on Nextstrain, a web-based visualization framework for real-time tracking of pathogen evolution. CHIKV molecular epidemiology reveals single nucleotide variants that change the stability and fold of locally stable RNA structures. We propose alternative RNA structure formation in different CHIKV lineages by predicting more than a dozen RNA elements that are subject to perturbation of the structure ensemble upon variation of a single nucleotide.

Structural modeling and phylogenetic analysis for infectious disease transmission pattern based on maximum likelihood tree approach

The contagious disease transmission pattern outbreak caused a massive human casualty and became a pandemic, as confirmed by the World Health Organization (WHO). The present research aims to understand the infectious disease transmission pattern outbreak due to molecular epidemiology. Hence, infected patients over time can spread infectious disease. The virus may develop further mutations, and that there might be a more toxic virulent strain, which leads to several environmental risk factors. Therefore, it is essential to monitor and characterize patient profiles, variants, symptoms, geographic locations, and treatment responses to analyze and evaluate infectious disease patterns among humans. This research proposes the Evolutionary tree analysis (ETA) for the molecular evolutionary genetic analysis to reduce medical risk factors. Furthermore, The Maximum likelihood tree method (MLTM) has been used to analyze the selective pressure, which is examined to identify a mutation that may influence the infectious disease transmission pattern's clinical progress. This study also utilizes ETA with Markov Chain Bayesian Statistics (MCBS) approach to reconstruct transmission trees with sequence information. The experimental shows that the proposed ETA-MCBS method achieves a 97.55% accuracy, prediction of 99.56%, and 98.55% performance compared to other existing methods.

Fundamentals of genomic epidemiology, lessons learned from the coronavirus disease 2019 (COVID-19) pandemic, and new directions

The coronavirus disease 2019 (COVID-19) pandemic was one of the significant causes of death worldwide in 2020. The disease is caused by severe acute coronavirus syndrome (SARS) coronavirus 2 (SARS-CoV-2), an RNA virus of the subfamily Orthocoronavirinae related to 2 other clinically relevant coronaviruses, SARS-CoV and MERS-CoV. Like other coronaviruses and several other viruses, SARS-CoV-2 originated in bats. However, unlike other coronaviruses, SARS-CoV-2 resulted in a devastating pandemic. The SARS-CoV-2 pandemic rages on due to viral evolution that leads to more transmissible and immune evasive variants. Technology such as genomic sequencing has driven the shift from syndromic to molecular epidemiology and promises better understanding of variants. The COVID-19 pandemic has exposed critical impediments that must be addressed to develop the science of pandemics. Much of the progress is being applied in the developed world. However, barriers to the use of molecular epidemiology in low- and middle-income countries (LMICs) remain, including lack of logistics for equipment and reagents and lack of training in analysis. We review the molecular epidemiology literature to understand its origins from the SARS epidemic (2002-2003) through influenza events and the current COVID-19 pandemic. We advocate for improved genomic surveillance of SARS-CoV and understanding the pathogen diversity in potential zoonotic hosts. This work will require training in phylogenetic and high-performance computing to improve analyses of the origin and spread of pathogens. The overarching goals are to understand and abate zoonosis risk through interdisciplinary collaboration and lowering logistical barriers.

Patch dynamics modeling framework from pathogens' perspective: Unified and standardized approach for complicated epidemic systems

Mathematical models are powerful tools to investigate, simulate, and evaluate potential interventions for infectious diseases dynamics. Much effort has focused on the Susceptible-Infected-Recovered (SIR)-type compartment models. These models consider host populations and measure change of each compartment. In this study, we propose an alternative patch dynamic modeling framework from pathogens' perspective. Each patch, the basic module of this modeling framework, has four standard mechanisms of pathogen population size change: birth (replication), death, inflow, and outflow. This framework naturally distinguishes between-host transmission process (inflow and outflow) and within-host infection process (replication) during the entire transmission-infection cycle. We demonstrate that the SIR-type model is actually a special cross-sectional and discretized case of our patch dynamics model in pathogens' viewpoint. In addition, this patch dynamics modeling framework is also an agent-based model from hosts' perspective by incorporating individual host's specific traits. We provide an operational standard to formulate this modular-designed patch dynamics model. Model parameterization is feasible with a wide range of sources, including genomics data, surveillance data, electronic health record, and from other emerging technologies such as multiomics. We then provide two proof-of-concept case studies to tackle some of the existing challenges of SIR-type models: sexually transmitted disease and healthcare acquired infections. This patch dynamics modeling framework not only provides theoretical explanations to known phenomena, but also generates novel insights of disease dynamics from a more holistic viewpoint. It is also able to simulate and handle more complicated scenarios across biological scales such as the current COVID-19 pandemic.

Whole genome sequencing of Plasmodium vivax isolates reveals frequent sequence and structural polymorphisms in erythrocyte binding genes

Plasmodium vivax malaria is much less common in Africa than the rest of the world because the parasite relies primarily on the Duffy antigen/chemokine receptor (DARC) to invade human erythrocytes, and the majority of Africans are Duffy negative. Recently, there has been a dramatic increase in the reporting of P. vivax cases in Africa, with a high number of them being in Duffy negative individuals, potentially indicating P. vivax has evolved an alternative invasion mechanism that can overcome Duffy negativity. Here, we analyzed single nucleotide polymorphism (SNP) and copy number variation (CNV) in Whole Genome Sequence (WGS) data from 44 P. vivax samples isolated from symptomatic malaria patients in southwestern Ethiopia, where both Duffy positive and Duffy negative individuals are found. A total of 123,711 SNPs were detected, of which 22.7% were nonsynonymous and 77.3% were synonymous mutations. The largest number of SNPs were detected on chromosomes 9 (24,007 SNPs; 19.4% of total) and 10 (16,852 SNPs, 13.6% of total). There were particularly high levels of polymorphism in erythrocyte binding gene candidates including merozoite surface protein 1 (MSP1) and merozoite surface protein 3 (MSP3.5, MSP3.85 and MSP3.9). Two genes, MAEBL and MSP3.8 related to immunogenicity and erythrocyte binding function were detected with significant signals of positive selection. Variation in gene copy number was also concentrated in genes involved in host-parasite interactions, including the expansion of the Duffy binding protein gene (PvDBP) on chromosome 6 and MSP3.11 on chromosome 10. Based on the phylogeny constructed from the whole genome sequences, the expansion of these genes was an independent process among the P. vivax lineages in Ethiopia. We further inferred transmission patterns of P. vivax infections among study sites and showed various levels of gene flow at a small geographical scale. The genomic features of P. vivax provided baseline data for future comparison with those in Duffy-negative individuals and allowed us to develop a panel of informative Single Nucleotide Polymorphic markers diagnostic at a micro-geographical scale.

Plasmodium vivax is the most geographically widespread parasite species that causes malaria in humans. Although it occurs in Africa as a member of a mix of Plasmodium species, P. vivax is dominant in other parts of the world outside of Africa (e.g., Brazil). It was previously thought that most African populations were immune to P. vivax infections due to the absence of Duffy antigen chemokine receptor (DARC) gene expression required for erythrocyte invasion. However, several recent reports have indicated the emergence and potential spread of P. vivax across human populations in Africa. Compared to Southeast Asia and South America where P. vivax is highly endemic, data on polymorphisms in erythrocyte binding gene candidates of P. vivax from Africa is limited. Filling this knowlege gap is critical for identifying functional genes in erythrocyte invasion, biomarkers for tracking the P. vivax isolates from Africa, as well as potential gene targets for vaccine development. This paper examined the level of genetic polymorphisms in a panel of 43 potential erythrocyte binding protein genes based on whole genome sequences and described transmission patterns of P. vivax infections from different study sites in Ethiopia based on the genetic variants. Our analyses showed that chromosomes 9 and 10 of the P. vivax genomes isolated in Ethiopia had the most high-quality genetic polymorphisms. Among all erythrocyte binding protein gene candidates, the merozoite surface proteins 1 and merozoite surface protein 3 showed high levels of polymorphism. MAEBL and MSP3.8 related to immunogenicity and erythrocyte binding function were detected with significant signals of positive selection. The expansion of the Duffy binding protein and merozoite surface protein 3 gene copies was an independent process among the P. vivax lineages in Ethiopia. Various levels of gene flow were observed even at a smaller geographical scale. Our study provided baseline data for future comparison with P. vivax in Duffy negative individuals and help develop a panel of genetic markers that are informative at a micro-geographical scale.

A Mutation Network Method for Transmission Analysis of Human Influenza H3N2

Characterizing the spatial transmission pattern is critical for better surveillance and control of human influenza. Here, we propose a mutation network framework that utilizes network theory to study the transmission of human influenza H3N2. On the basis of the mutation network, the transmission analysis captured the circulation pattern from a global simulation of human influenza H3N2. Furthermore, this method was applied to explore, in detail, the transmission patterns within Europe, the United States, and China, revealing the regional spread of human influenza H3N2. The mutation network framework proposed here could facilitate the understanding, surveillance, and control of other infectious diseases.

Updated Phylogeny of Chikungunya Virus Suggests Lineage-Specific RNA Architecture

Chikungunya virus (CHIKV), a mosquito-borne alphavirus of the family Togaviridae, has recently emerged in the Americas from lineages from two continents: Asia and Africa. Historically, CHIKV circulated as at least four lineages worldwide with both enzootic and epidemic transmission cycles. To understand the recent patterns of emergence and the current status of the CHIKV spread, updated analyses of the viral genetic data and metadata are needed. Here, we performed phylogenetic and comparative genomics screens of CHIKV genomes, taking advantage of the public availability of many recently sequenced isolates. Based on these new data and analyses, we derive a revised phylogeny from nucleotide sequences in coding regions. Using this phylogeny, we uncover the presence of several distinct lineages in Africa that were previously considered a single one. In parallel, we performed thermodynamic modeling of CHIKV untranslated regions (UTRs), which revealed evolutionarily conserved structured and unstructured RNA elements in the 3'UTR. We provide evidence for duplication events in recently emerged American isolates of the Asian CHIKV lineage and propose the existence of a flexible 3'UTR architecture among different CHIKV lineages.