Evolution Of Pathogens Research Articles

How cultural innovations trigger the emergence of new pathogens

Cultural practices perceived to be adaptive—from clearing land for food production to medical innovations—can disseminate quickly through human populations. However, these same practices often have unintended maladaptive effects. A particularly consequential effect is the emergence of diseases. In numerous instances, a cultural change is followed by the appearance of a new pathogen. Here, we develop mathematical models to analyze the population processes through which cultural evolution precipitates the emergence of a new disease. We find that when a risk-bearing cultural practice spreads, emergence can be an unavoidable cost even if a safer alternative practice eventually evolves from the original. Social learning and a fitness advantage associated with the evolving practice drive early disease emergence but the two factors have distinct effects on the time to mutation of the pathogen and significant stochastic variation is observed. For example, a disease can take longer to emerge in a population that adopts the risk-bearing practice quickly than in a population that is slow to transition. Extending the model to explore the effects of an alternative practice evolving from the original, we find a nonmonotonic relationship between relative risk of the two practices and the median time to disease emergence. Our findings contribute to understanding how cultural evolution can shape pathogen evolution and highlight the unpredictability of disease emergence.

Frequent genetic exchanges revealed by a pan-mitogenome graph of a fungal plant pathogen.

Mitochondria are present in almost all eukaryotic lineages. The mitochondrial genomes (mitogenomes) evolve separately from nuclear genomes, and they can therefore provide relevant insights into the evolution of their host species. Fusarium oxysporum is a major fungal plant pathogen that is assumed to reproduce clonally. However, horizontal chromosome transfer between strains can occur through heterokaryon formation, and recently, signs of sexual recombination have been observed. Similarly, signs of recombination in F. oxysporum mitogenomes challenged the prevailing assumption of clonal reproduction in this species. Here, we construct, to our knowledge, the first fungal pan-mitogenome graph of nearly 500 F. oxysporum mitogenome assemblies to uncover the variation and evolution. In general, the gene order of fungal mitogenomes is not well conserved, yet the mitogenome of F. oxysporum and related species are highly colinear. We observed two strikingly contrasting regions in the F. oxysporum pan-mitogenome, comprising a highly conserved core mitogenome and a long variable region (6-16 kb in size), of which we identified three distinct types. The pan-mitogenome graph reveals that only five intron insertions occurred in the core mitogenome and that the long variable regions drive the difference between mitogenomes. Moreover, we observed that their evolution is neither concurrent with the core mitogenome nor with the nuclear genome. Our large-scale analysis of long variable regions uncovers frequent recombination between mitogenomes, even between strains that belong to different taxonomic clades. This challenges the common assumption of incompatibility between genetically diverse F. oxysporum strains and provides new insights into the evolution of this fungal species.IMPORTANCEInsights into plant pathogen evolution is essential for the understanding and management of disease. Fusarium oxysporum is a major fungal pathogen that can infect many economically important crops. Pathogenicity can be transferred between strains by the horizontal transfer of pathogenicity chromosomes. The fungus has been thought to evolve clonally, yet recent evidence suggests active sexual recombination between related isolates, which could at least partially explain the horizontal transfer of pathogenicity chromosomes. By constructing a pan-genome graph of nearly 500 mitochondrial genomes, we describe the genetic variation of mitochondria in unprecedented detail and demonstrate frequent mitochondrial recombination. Importantly, recombination can occur between genetically diverse isolates from distinct taxonomic clades and thus can shed light on genetic exchange between fungal strains.

Analysis of Acinetobacter P-type type IV secretion system-encoding plasmid diversity uncovers extensive secretion system conservation and diverse antibiotic resistance determinants.

Acinetobacter baumannii is globally recognized as a multi-drug-resistant pathogen of critical concern due to its capacity for horizontal gene transfer and resistance to antibiotics. Phylogenetically diverse Acinetobacter species mediate human infection, including many considered as important emerging pathogens. While globally recognized as a pathogen of concern, pathogenesis mechanisms are poorly understood. P-type type IV secretion systems (T4SSs) represent important drivers of pathogen evolution, responsible for horizontal gene transfer and secretion of proteins that mediate host-pathogen interactions, contributing to pathogen survival, antibiotic resistance, virulence, and biofilm formation. Genes encoding a P-type T4SS were previously identified on plasmids harboring the carbapenemase gene blaNDM-1 in several clinically problematic Acinetobacter; however, their prevalence among the genus, geographical distribution, the conservation of T4SS proteins, and full capacity for resistance genes remain unclear. Using systematic analyses, we show that these plasmids belong to a group of 53 P-type T4SS-encoding plasmids in 20 established Acinetobacter species, the majority of clinical relevance, including diverse A. baumannii sequence types and one strain of Providencia rettgeri. The strains were globally distributed in 14 countries spanning five continents, and the conjugative operon's T4SS proteins were highly conserved in most plasmids. A high proportion of plasmids harbored resistance genes, with 17 different genes spanning seven drug classes. Collectively, this demonstrates that P-type T4SS-encoding plasmids are more widespread among the Acinetobacter genus than previously anticipated, including strains of both clinical and environmental importance. This research provides insight into the spread of resistance genes among Acinetobacter and highlights a group of plasmids of importance for future surveillance.

Genome sequences for twenty-four Phytophthora and one Nothophytophthora species for the study of the evolution of pathogenicity in Peronosporaceae

Oomycetes classified in the genera Phytophthora and Nothophytophthora encompass a wide range of lifestyles, from saprotrophic and water-borne to destructive soil-borne or wind-dispersed plant pathogens. To clarify the evolutionary and genomic basis of these transitions, genome sequences for a wide range of species are necessary. However, the amount of genomes currently available is not representative of the full range of these lifestyles. To address this gap, we present draft genomes of 24 Phytophthora and one Nothophytophthora species, of which 14 have 100% BUSCO completeness for the Straminipila dataset. We hope that this resource will stimulate further research into the evolution of pathogenicity in Peronosporaceae.

Crispr and plant pathology: Revolutionizing disease resistance in crops

CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) technology has revolutionized plant pathology by providing a precise and efficient tool for enhancing disease resistance in crops. This gene-editing technique enables scientists to modify specific DNA sequences in plants, allowing for the targeted improvement of traits related to pathogen defense. By altering genes responsible for susceptibility to diseases, CRISPR facilitates the development of crops that are more resistant to bacterial, fungal, and viral pathogens, thereby reducing the reliance on chemical pesticides. Additionally, CRISPR can be used to boost plant immunity and improve resilience against emerging plant diseases that threaten global food security. The technology's accuracy and speed have accelerated breeding programs, enabling researchers to respond rapidly to agricultural challenges posed by climate change and the evolution of new pathogens. This article explores the breakthroughs achieved through CRISPR in plant pathology, highlighting case studies of its application in major crops such as rice, wheat, and tomatoes. Furthermore, it discusses the ethical, regulatory, and environmental considerations of using CRISPR for crop improvement, alongside its potential to revolutionize sustainable agriculture by reducing disease-induced yield losses and promoting food security.

Distinct impacts of each anti-anti-sigma factor ortholog of the chlamydial Rsb partner switching mechanism on development in Chlamydia trachomatis.

Partner switching mechanisms (PSMs) are signal transduction systems comprised of a sensor phosphatase (RsbU), an anti-sigma factor (RsbW, kinase), an anti-anti-sigma factor (RsbV, the RsbW substrate), and a target sigma factor. Chlamydia spp. are obligate intracellular bacterial pathogens of animals that undergo a developmental cycle transitioning between the infectious elementary body (EB) and replicative reticulate body (RB) within a host cell-derived vacuole (inclusion). Secondary differentiation events (RB to EB) are transcriptionally regulated, in part, by the housekeeping sigma factor (σ66) and two late-gene sigma factors (σ54 and σ28). Prior research supports that the PSM in Chlamydia trachomatis regulates availability of σ66. Pan-genome analysis revealed that PSM components are conserved across the phylum Chlamydiota, with Chlamydia spp. possessing an atypical arrangement of two anti-anti-sigma factors, RsbV1 and RsbV2. Bioinformatic analyses support RsbV2 as the homolog to the pan-genome-conserved RsbV with RsbV1 as an outlier. This, combined with in vitro data, indicates that RsbV1 and RsbV2 are structurally and biochemically distinct. Reduced levels or overexpression of RsbV1/RsbV2 did not significantly impact C. trachomatis growth or development. In contrast, overexpression of a non-phosphorylatable RsbV2 S55A mutant, but not overexpression of an RsbV1 S56A mutant, resulted in a 3 log reduction in infectious EB production without reduction in genomic DNA (total bacteria) or inclusion size, suggesting a block in secondary differentiation. The block was corroborated by reduced production of σ54/28-regulated late proteins and via transmission electron microscopy.IMPORTANCEChlamydia trachomatis is the leading cause of reportable bacterial sexually transmitted infections (STIs) and causes the eye infection trachoma, a neglected tropical disease. Broad-spectrum antibiotics used for treatment can lead to microbiome dysbiosis and increased antibiotic resistance development in other bacteria, and treatment failure for chlamydial STIs is a recognized clinical problem. Here, we show that disruption of a partner switching mechanism (PSM) significantly reduces infectious progeny production via blockage of reticulate body to elementary body differentiation. We also reveal a novel PSM expansion largely restricted to the species infecting animals, suggesting a role in pathogen evolution. Collectively, our results highlight the chlamydial PSM as a key regulator of development that could be a potential target for novel therapeutics.

Pangenome graph analysis reveals extensive effector copy-number variation in spinach downy mildew.

Plant pathogens adapt at speeds that challenge contemporary disease management strategies like the deployment of disease resistance genes. The strong evolutionary pressure to adapt, shapes pathogens' genomes, and comparative genomics has been instrumental in characterizing this process. With the aim to capture genomic variation at high resolution and study the processes contributing to adaptation, we here leverage an innovative, multi-genome method to construct and annotate the first pangenome graph of an oomycete plant pathogen. We expand on this approach by analysing the graph and creating synteny based single-copy orthogroups for all genes. We generated telomere-to-telomere genome assemblies of six genetically diverse isolates of the oomycete pathogen Peronospora effusa, the economically most important disease in cultivated spinach worldwide. The pangenome graph demonstrates that P. effusa genomes are highly conserved, both in chromosomal structure and gene content, and revealed the continued activity of transposable elements which are directly responsible for 80% of the observed variation between the isolates. While most genes are generally conserved, virulence related genes are highly variable between the isolates. Most of the variation is found in large gene clusters resulting from extensive copy-number expansion. Pangenome graph-based discovery can thus be effectively used to capture genomic variation at exceptional resolution, thereby providing a framework to study the biology and evolution of plant pathogens.

Control of fungal diseases of tomato (<i>Lycopersicum esculentum</i> Mill) fruits using various plant extracts

Plant harmful fungi induce symptoms of illnesses that significantly impair the quantity and quality of tomato (Lycopersicum esculentum) yields. The high-water composition of tomatoes renders it highly vulnerable to fungal decay. These fungi, responsible for the decay of tomatoes, generate mycotoxins that pose serious risks to human health. Thus, this research goal is to separate, characterize, and classify the fungi linked with the decline of tomato produce sold across four markets in Mkpat Enin and Ikot Abasi Local Government Areas of Akwa Ibom State, Nigeria. Among the fungal pathogens extracted from afflicted tomato fruits were Fusarium moniliformes, Rhizopus stolonifera, and Aspergillus alternata. Different concentrations of the extracts were individually introduced into Potato Dextrose Agar media. The fungal pathogens were at that point individually introduced into the media and left to incubate for 7 days. Findings revealed that P < 0.05 suppressed the mycelial evolution of the fungal pathogens at a greater concentration tested, with the extent of inhibition varying among different extracts. The results concerning the proportion inhibition of plant extracts on different fungus indicated that, at concentrations ranging from 40% to 80%, ethanolic extracts derived from Cola acuminata and Zingiber officinale significantly (p<0.05) restrained the growth of F. moniliformes, R. stolonifera, and A. alternata. Specifically, the ethanolic leaf extract of C. acuminata demonstrated moderate inhibition on A. alternata at 60%, while the ethanolic extract of Zingiber officinale exhibited low inhibition on F. moniliformes at 40%. At a concentration of 60% in ethanolic extracts, F. moniliformes experienced the greatest inhibition among the plant extracts, whereas A. alternata displayed the least inhibition. Pathogenicity testing indicated that Aspergillus alternata exhibited the largest decay of 25mm in diameter in a healthy tomato fruit, while Rhizopus stolonifera had the smallest decay diameter. Thus, to cover the ledge life of tomato fruits, therefore there’s adequate need to implement proper handling techniques and utilize adequate storage facilities.

Mathematical Models for Infectious Disease Dynamics and Control Strategies

The study explores mathematical models related to the dynamics of infectious diseases and approaches to manage them. These models are essential resources for comprehending how illnesses spread throughout people and assessing how well control strategies work. The study of infectious disease epidemiology heavily relies on mathematical modeling and analysis. Here, we give a clear overview of the spread of disease, explain how to mathematically model this stochastic process, and show how to utilize this mathematical representation to analyze the emergent dynamics of real-world epidemics. The advancement of mathematical analysis and modeling is crucial to our expanding comprehension of the evolution and ecology of pathogens. This study emphasizes how important mathematical modeling is to improving our knowledge of the dynamics of infectious diseases and how crucial it is to creating efficient management plans to lessen the burden of infectious diseases on public health.

Genome resource announcement for emerging pathogen Bipolaris gigantea, isolated from Microstegium vimineum

Bipolaris gigantea is a pathogen of the invasive grass Microstegium vimineum and an emerging pathogen of other hosts such as hemp and barley, causing characteristic eyespot foliar lesions. The fungus is characterized by long pale hyaline conidia measuring about 300 to 350 μm. Previously, this pathogen was classified in the Drechslera genus, and recently reassigned as Bipolaris based on molecular identification. Here, we generated a high-quality draft genome sequence of B. gigantea isolate BGF using long and short read DNA sequencing. The assembled genome, 30.23 Mb in size with a BUSCO completeness score of 98.4%, exhibited synteny with the common grass pathogen B. sorokiniana isolate 10943. Average nucleotide identity (ANI) and single nucleotide polymorphisms (SNP) analyses revealed high sequence identity with B. gigantea isolates from Cannabis sativa fields in Kentucky. This research provides a genomic resource that will contribute to future studies to understand the host range evolution and pathogenicity of this novel pathogen.

Revealing SARS-CoV-2 Mpro mutation cold and hot spots: Dynamic residue network analysis meets machine learning

Deciphering the effect of evolutionary mutations of viruses and predicting future mutations is crucial for designing long-lasting and effective drugs. While understanding the impact of current mutations on protein drug targets is feasible, predicting future mutations due to natural evolution of viruses and environmental pressures remains challenging. Here, we leveraged existing mutation data during the evolution of the SARS-CoV-2 protein drug target main protease (Mpro) to test the predictive power of dynamic residue network (DRN) analysis in identifying mutation cold and hot spots. We conducted molecular dynamics simulations on the Mpro of SARS-CoV-2 (Wuhan strain) and calculated eight DRN metrics (averaged BC, CC, DC, EC, ECC, KC, L, PR), each of which identifies a unique network feature within the protein. The sets of residues with the highest and lowest values for each metric, comprising potential cold and hot spots, were compared to published biochemical analyses and per residue mutation frequencies observed across five SARS-CoV-2 lineages, encompassing a total of 191,878 sequences. Individual DRN metrics displayed only modest power to predict the mutation frequency of individual residues. However, integrating the eight DRN metrics with additional structural and sequence-derived metrics allowed us to develop machine learning models which significantly improved the prediction of residue mutation frequency. While further refinements should enhance accuracy, we demonstrated a robust method to understand pathogen evolution. This approach can also guide the development of long-lasting drugs by targeting functional residues located in and near active site, and allosteric sites, that are less prone to mutations.

Pathogens from salmon aquaculture in relation to conservation of wild Pacific salmon in Canada.

The spread of pathogens from farmed salmon is a conservation concern for wild Pacific salmon in British Columbia (BC), Canada. Three pathogens are prevalent in farmed Atlantic salmon in BC, spill over to wild Pacific salmon, and are linked to negative impacts on wild salmon: Piscine orthoreovirus, Tenacibaculum spp., and sea lice (Lepeophtheirus salmonis). Molecular screening of infectious agents in farmed and wild salmon and environmental DNA highlights a further 4 agents that are likely elevated near salmon farms and 37 that co-occur in wild and farmed salmon. Pathogens likely affect wild salmon indirectly by mediating migration, competition, and predation. Current net-pen aquaculture practices pose these risks to numerous populations of all species of wild salmon in BC, most of which are not covered in Government of Canada science and advisory reports. Climate change, pathogen evolution, and changes to disease management and aquaculture regulations will influence future risks.

Genomics and Bioinformatics in One Health: Transdisciplinary Approaches for Health Promotion and Disease Prevention.

The One Health concept underscores the interconnectedness of human, animal, and environmental health, necessitating an integrated, transdisciplinary approach to tackle contemporary health challenges. This perspective paper explores the pivotal role of genomics and bioinformatics in advancing One Health initiatives. By leveraging genomic technologies and bioinformatics tools, researchers can decode complex biological data, enabling comprehensive insights into pathogen evolution, transmission dynamics, and host-pathogen interactions across species and environments (or ecosystems). These insights are crucial for predicting and mitigating zoonotic disease outbreaks, understanding antimicrobial resistance patterns, and developing targeted interventions for health promotion and disease prevention. Furthermore, integrating genomic data with environmental and epidemiological information enhances the precision of public health responses. Here we discuss case studies demonstrating successful applications of genomics and bioinformatics in One Health contexts, such as including data integration, standardization, and ethical considerations in genomic research. By fostering collaboration among geneticists, bioinformaticians, epidemiologists, zoologists, and data scientists, the One Health approach can harness the full potential of genomics and bioinformatics to safeguard global health. This perspective underscores the necessity of continued investment in interdisciplinary education, research infrastructure, and policy frameworks to effectively employ these technologies in the service of a healthier planet.

Chronic infections can generate SARS-CoV-2-like bursts of viral evolution without epistasis.

Multiple SARS-CoV-2 variants have arisen during the first years of the pandemic, often bearing many new mutations. Several explanations have been offered for the surprisingly sudden emergence of multiple mutations that enhance viral fitness, including cryptic transmission, spillover from animal reservoirs, epistasis between mutations, and chronic infections. Here, we simulated pathogen evolution combining within-host replication and between-host transmission. We found that, under certain conditions, chronic infections can lead to SARS-CoV-2-like bursts of mutations even without epistasis. Chronic infections can also increase the global evolutionary rate of a pathogen even in the absence of clear mutational bursts. Overall, our study supports chronic infections as a plausible origin for highly mutated SARS-CoV-2 variants. More generally, we also describe how chronic infections can influence pathogen evolution under different scenarios.

Antibiotic-producing plant-associated bacteria, anti-virulence therapy and microbiome engineering: Integrated approaches in sustainable agriculture.

Plant health is crucial for maintaining the well-being of humans, animals and the environment. Plant pathogens pose significant challenges to agricultural production, global food security and ecosystem biodiversity. This problem is exacerbated by the impact of climate change, which is expected to alter the emergence and evolution of plant pathogens and their interaction with their plant hosts. Traditional approaches to managing phytopathogens involved the use of chemical pesticides, but alternative strategies are needed to address their ongoing decline in performance as well as their negative impact on the environment and public health. Here, we highlight the advancement and effectiveness of biocontrol strategies based on the use of antimicrobial-producing plant-associated bacteria, anti-virulence therapy (e.g. quorum quenching) and microbiome engineering as sustainable biotechnological approaches to promote plant health and foster sustainable agriculture. Notably, Enterobacterales are emerging as important biocontrol agents and as a source of new antimicrobials for potential agricultural use. We analysed here the genomes of over 250 plant-associated enterobacteria to examine their potential to synthesize secondary metabolites. Exploration of the plant microbiome is of major interest in the search for eco-friendly alternatives for reducing the use of chemical pesticides.

Artificial intelligence-based prediction of pathogen emergence and evolution in the world of synthetic biology.

The emergence of new techniques in both microbial biotechnology and artificial intelligence (AI) is opening up a completely new field for monitoring and sometimes even controlling the evolution of pathogens. However, the now famous generative AI extracts and reorganizes prior knowledge from large datasets, making it poorly suited to making predictions in an unreliable future. In contrast, an unfamiliar perspective can help us identify key issues related to the emergence of new technologies, such as those arising from synthetic biology, whilst revisiting old views of AI or including generative AI as a generator of abduction as a resource. This could enable us to identify dangerous situations that are bound to emerge in the not-too-distant future, and prepare ourselves to anticipate when and where they will occur. Here, we emphasize the fact that amongst the many causes of pathogen outbreaks, often driven by the explosion of the human population, laboratory accidents are a major cause of epidemics. This review, limited to animal pathogens, concludes with a discussion of potential epidemic origins based on unusual organisms or associations of organisms that have rarely been highlighted or studied.

Spatial Epidemiology and Its Role in Prevention and Control of Swine Viral Disease

Spatial epidemiology offers a comprehensive framework for analyzing the spatial distribution and transmission of diseases, leveraging advanced technical tools and software, including Geographic Information Systems (GISs), remote sensing technology, statistical and mathematical software, and spatial analysis tools. Despite its increasing application to swine viral diseases (SVDs), certain challenges arise from its interdisciplinary nature. To support novices, frontline veterinarians, and public health policymakers in navigating its complexities, we provide a comprehensive overview of the common applications of spatial epidemiology in SVD. These applications are classified into four categories based on their objectives: visualizing and elucidating spatiotemporal distribution patterns, identifying risk factors, risk mapping, and tracing the spatiotemporal evolution of pathogens. We further elucidate the technical methods, software, and considerations necessary to accomplish these objectives. Additionally, we address critical issues such as the ecological fallacy and hypothesis generation in geographic correlation analysis. Finally, we explore the future prospects of spatial epidemiology in SVD within the One Health framework, offering a valuable reference for researchers engaged in the spatial analysis of SVD and other epidemics.

Changes in DNA methylation contribute to rapid adaptation in bacterial plant pathogen evolution.

Adaptation is usually explained by beneficial genetic mutations that are transmitted from parents to offspring and become fixed in the adapted population. However, genetic mutation analysis alone is not sufficient to fully explain the adaptive processes, and several studies report the existence of nongenetic (or epigenetic) inheritance that can enable adaptation to new environments. In the present work, we tested the hypothesis of the role of DNA methylation, a form of epigenetic modification, in adaptation of the plant pathogen Ralstonia pseudosolanacearum to the host during experimental evolution. Using SMRT-seq technology, we analyzed the methylomes of 31 experimentally evolved clones obtained after serial passages on 5 different plant species during 300 generations. Comparison with the methylome of the ancestral clone revealed a list of 50 differential methylated sites (DMSs) at the GTWWAC motif. Gene expression analysis of the 39 genes targeted by these DMSs revealed limited correlation between differential methylation and differential expression of the corresponding genes. Only 1 gene showed a correlation, the RSp0338 gene encoding the EpsR regulator protein. The MSRE-qPCR technology, used as an alternative approach for DNA methylation analysis, also found the 2 DMSs upstream RSp0338. Using site-directed mutagenesis, we demonstrated the contribution of these 2 DMSs in host adaptation. As these DMSs appeared very early in the experimental evolution, we hypothesize that such fast epigenetic changes can allow rapid adaptation to the plant stem environment. In addition, we found that the change in DNA methylation upstream RSp0338 remains stable at least for 100 generations outside the host and thus can contribute to long-term adaptation to the host plant. To our knowledge, this is the first study showing a direct link between bacterial epigenetic variation and adaptation to a new environment.

The evolutionary features and roles of single nucleotide variants and charged amino acid mutations in influenza outbreaks during NPI period

The epidemic and outbreaks of influenza B Victoria lineage (Bv) during 2019–2022 led to an analysis of genetic, epitopes, charged amino acids and Bv outbreaks. Based on the National Influenza Surveillance Network (NISN), the Bv 72 strains isolated during 2019–2022 were selected by spatio-temporal sampling, then were sequenced. Using the Compare Means, Correlate and Cluster, the outbreak data were analyzed, including the single nucleotide variant (SNV), amino acid (AA), epitope, evolutionary rate (ER), Shannon entropy value (SV), charged amino acid and outbreak. With the emergence of COVID-19, the non-pharmaceutical interventions (NPIs) made Less distant transmission and only Bv outbreak. The 2021–2022 strains in the HA genes were located in the same subset, but were distinct from the 2019–2020 strains (P < 0.001). The codon G → A transition in nucleotide was in the highest ratio but the transversion of C → A and T → A made the most significant contribution to the outbreaks, while the increase in amino acid mutations characterized by polar, acidic and basic signatures played a key role in the Bv epidemic in 2021–2022. Both ER and SV were positively correlated in HA genes (R = 0.690) and NA genes (R = 0.711), respectively, however, the number of mutations in the HA genes was 1.59 times higher than that of the NA gene (2.15/1.36) from the beginning of 2020 to 2022. The positively selective sites 174, 199, 214 and 563 in HA genes and the sites 73 and 384 in NA genes were evolutionarily selected in the 2021–2022 influenza outbreaks. Overall, the prevalent factors related to 2021–2022 influenza outbreaks included epidemic timing, Tv, Ts, Tv/Ts, P137 (B → P), P148 (B → P), P199 (P → A), P212 (P → A), P214 (H → P) and P563 (B → P). The preference of amino acid mutations for charge/pH could influence the epidemic/outbreak trends of infectious diseases. Here was a good model of the evolution of infectious disease pathogens. This study, on account of further exploration of virology, genetics, bioinformatics and outbreak information, might facilitate further understanding of their deep interaction mechanisms in the spread of infectious diseases.

Factors Contributing to Emergence of infectious viral diseases in India: Issues and Challenges after COVID-19 Pandemic

Emerging and re-emerging viral infections are major cause of morbidity and mortality in humans and animals. India had experienced numerous infectious disease outbreaks and epidemics in past years. However, tremendous strides have been achieved in the past in the fight against serious epidemic diseases. It has been found that a wide range of complex factors, such as pathogen evolution, human invasion, commerce in wild animals, microbial adaptation, changes in the environment and dynamic interactions between humans and animals influence the emergence and transmission of infectious viral diseases. As the COVID-19 pandemic demonstrated, India's secondary and tertiary health-care system is quite advanced. The study of infectious diseases, in particular their pathogenesis, genetic profile and diagnosis has fundamentally changed with the advent of genome sequencing and nucleic acid detection technology. Additionally, advance therapy and vaccination led to best possible patient management and care. Further scientific investigations and research are needed to discover neglected diseases that have the potential to cause epidemics as well as to develop updated vaccines, modern treatment strategy and diagnostics at molecular level. This evaluation will aid for policymakers, academics and researchers to redesign the course of action to combat the deadly emerging pathogenic viruses and also preserve the ecosystem.