Pathogen Genomes Research Articles

Novel recombinant SARS-CoV-2 lineage detected through genomic surveillance in Wales, UK.

Recombination, the process whereby a segment of genetic material from one genome is inserted into another, producing a new chimeric genome, is an important evolutionary mechanism frequently observed in coronaviruses. The risks posed by recombination include the shuffling of advantageous mutations that may increase transmissibility, severity or vaccine escape. We present a genomic and epidemiological description of a new recombinant lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), XR, first identified in Wales. The Pathogen Genomics Unit (Public Health Wales, UK) sequences positive SARS-CoV-2 PCR tests using the ARTIC SARS-CoV-2 sequencing protocol. Recombinants were detected using an in-house pipeline and the epidemiological data analysed in R. Nosocomial cases were defined as those with samples taken after >7 days in hospital. Between February and March 2022, we identified 78 samples with highly similar genomes, comprising a BA.1-like 5' end, a BA.2-like 3' end and a BA.2-like spike protein. This signature is consistent with recombination and was defined as XR by Pangolin (PANGO v1.8). A total of 50 % of cases had a sample collected whilst in hospital and the first three cases were immunocompromised patients. The patient median age was 58 years (range: 4-95 years) and most of the patients were fully vaccinated against SARS-CoV-2 (74 % third dose/booster). Three patients died within 28 days of their sample collection date, one of whom had COVID-19 listed amongst ICD10 (International Classification of Diseases 10) coded causes of death. Our integrated system enabled real-time monitoring of recombinant SARS-CoV-2 for early detection, in order to rapidly risk assess and respond. This work highlights the importance of setting-based surveillance of recombinant SARS-CoV-2, as well as the need to monitor immunocompromised populations through repeat testing and sequencing.

ПРОФЕССИОНАЛЬНЫЕ НАВЫКИ И ПРОФИЛЬ СПЕЦИАЛИСТА В ОБЛАСТИ МЕДИЦИНСКОЙ МИКРОБИОЛОГИИ (ОБЗОР ЛИТЕРАТУРЫ)

The article discusses the profile and professional skills of a specialist in the field of medical microbiology. The recent trend towards the centralization of microbiological laboratories in order to increase the level of funding, equipment, increase the range of studies performed and to standardize all stages of laboratory diagnostics (preanalytical, analytical and postanalytical) requires a revision of the qualification requirements for medical personnel. The authors raise the issue of a professional standard in the field of medical microbiology and analyze changes in the professional tasks of a medical microbiologist from the period of approval of the first curriculum in medical microbiology to the current stage in the development of laboratory diagnostics of infectious diseases. The basic competencies, obligatory knowledge and skills of a specialist in the field of medical microbiology are discussed, these are necessary for the implementation of job functions in the field of high-technological research methods using the genome of pathogens and microbial communities. The profile of a specialist is considered in terms of interaction with doctors of other specialties for the effective decision of medical problems in antimicrobial therapy and the prevention of infectious diseases. The search for literature sources was carried out using the Scopus, Web of Science, MedLine, Cochrane Library, EMBASE, GlobalHealth, CyberLeninka, and RSCI databases. The study showed that the professional skills of a medical microbiologist should be evaluated together with the specialist’s personal characteristics, which become necessary for graduates’ successful certification in higher medical educational institutions

Infectious disease in the Pleistocene: Old friends or old foes?

The impact of endemic and epidemic disease on humans has traditionally been seen as a comparatively recent historical phenomenon associated with the Neolithisation of human groups, an increase in population size led by sedentarism, and increasing contact with domesticated animals as well as species occupying opportunistic symbiotic and ectosymbiotic relationships with humans. The orthodox approach is that Neolithisation created the conditions for increasing population size able to support a reservoir of infectious disease sufficient to act as selective pressure. This orthodoxy is the result of an overly simplistic reliance on skeletal data assuming that no skeletal lesions equated to a healthy individual, underpinned by the assumption that hunter-gatherer groups were inherently healthy while agricultural groups acted as infectious disease reservoirs. The work of van Blerkom, Am. J. Phys. Anthropol., vol. suppl 37 (2003), Wolfe et al., Nature, vol. 447 (2007) and Houldcroft and Underdown, Am. J. Phys. Anthropol., vol. 160, (2016) has changed this landscape by arguing that humans and pathogens have long been fellow travelers. The package of infectious diseases experienced by our ancient ancestors may not be as dissimilar to modern infectious diseases as was once believed. The importance of DNA, from ancient and modern sources, to the study of the antiquity of infectious disease, and its role as a selective pressure cannot be overstated. Here we consider evidence of ancient epidemic and endemic infectious diseases with inferences from modern and ancient human and hominin DNA, and from circulating and extinct pathogen genomes. We argue that the pandemics of the past are a vital tool to unlock the weapons needed to fight pandemics of the future.

Key Advances in the New Era of Genomics-Assisted Disease Resistance Improvement of Brassica Species.

Disease resistance improvement remains a major focus in breeding programs as diseases continue to devastate Brassica production systems due to intensive cultivation and climate change. Genomics has paved the way to understand the complex genomes of Brassicas, which has been pivotal in the dissection of the genetic underpinnings of agronomic traits driving the development of superior cultivars. The new era of genomics-assisted disease resistance breeding has been marked by the development of high-quality genome references, accelerating the identification of disease resistance genes controlling both qualitative (major) gene and quantitative resistance. This facilitates the development of molecular markers for marker assisted selection and enables genome editing approaches for targeted gene manipulation to enhance the genetic value of disease resistance traits. This review summarizes the key advances in the development of genomic resources for Brassica species, focusing on improved genome references, based on long-read sequencing technologies and pangenome assemblies. This is further supported by the advances in pathogen genomics, which have resulted in the discovery of pathogenicity factors, complementing the mining of disease resistance genes in the host. Recognizing the co-evolutionary arms race between the host and pathogen, it is critical to identify novel resistance genes using crop wild relatives and synthetic cultivars or through genetic manipulation via genome-editing to sustain the development of superior cultivars. Integrating these key advances with new breeding techniques and improved phenotyping using advanced data analysis platforms will make disease resistance improvement in Brassica species more efficient and responsive to current and future demands.

Whole genome sequencing of Wilsonomyces carpophilus, an incitant of shot hole disease in stone fruits: insights into secreted proteins of a necrotrophic fungal repository.

Shot hole is one of the important fungal diseases in stone fruits viz., peach, plum, apricot and cherry caused by Wilsonomyces carpophilus and almond among nut crops. Fungicides significantly decrease the disease. Pathogenicity studies proved a wide host range of the pathogen infecting all stone fruits and almond among the nut crops, however, the mechanism underlying host-pathogen interaction is still unknown. Molecular detection of the pathogen using polymerase chain reaction (PCR) based simple sequence repeat (SSR) markers is also unknown due to the unavailability of the pathogen genome. We examined the morphology, pathology and genomics of the Wilsonomyces carpophilus. Whole genome sequencing of the W. carpophilus was carried out by Illumina HiSeq and PacBio high throughput sequencing plate-forms through hybrid assembly. Constant selection pressure alters the molecular mechanism of the pathogen causing disease. The studies revealed that the necrotrophs are more lethal with a complex pathogenicity mechanism and little-understood effector repositories. The different isolates of necrotrophic fungus W. carpophilus causing shot hole in stone fruits namely peach, plum, apricot and cherry, and almonds among the nut crops showed a significant variation in their morphology, however, the probability value (p = 0.29) suggests in-significant difference in the pathogenicity. Here, we reported draft genome of W. carpophilus of size 29.9Mb (Accession number: PRJNA791904). A total of 10,901 protein-coding genes were predicted, including heterokaryon incompatibility genes, cytochrome-p450 genes, kinases, sugar transporters among others. We found 2851 simple sequence repeats (SSRs), tRNAs, rRNAs and pseudogenes in the genome. The most prominent proteins showing necrotrophic lifestyle of the pathogen were hydrolases, polysaccharide-degrading enzymes, esterolytic, lipolytic, and proteolytic enzymes accounted for 225 released proteins. Among the 223 fungal species, top-hit species distribution revealed the majority of hits against the Pyrenochaeta species followed by Ascochyta rabiei and Alternaria alternata. Draft genome of W. carpophilus is 29.9Mb based on Illumina HiSeq and PacBio hybrid assembly. The necrotrophs are more lethal with a complex pathogenicity mechanism. A significant variation in morphology was observed in different pathogen isolates. A total of 10,901 protein-coding genes were predicted in the pathogen genome including heterokaryon incompatibility, cytochrome-p450 genes, kinases and sugar transporters. We found 2851 SSRs, tRNAs, rRNAs and pseudogenes, and prominent proteins showing necrotrophic lifestyle such as hydrolases, polysaccharide-degrading enzymes, esterolytic, lipolytic and proteolytic enzymes. The top-hit species distribution were against the Pyrenochaeta spp. followed by Ascochyta rabiei.

Agnostic Sequencing for Detection of Viral Pathogens.

The advent of next-generation sequencing (NGS) technologies has expanded our ability to detect and analyze microbial genomes and has yielded novel molecular approaches for infectious disease diagnostics. While several targeted multiplex PCR and NGS-based assays have been widely used in public health settings in recent years, these targeted approaches are limited in that they still rely on a priori knowledge of a pathogen's genome, and an untargeted or unknown pathogen will not be detected. Recent public health crises have emphasized the need to prepare for a wide and rapid deployment of an agnostic diagnostic assay at the start of an outbreak to ensure an effective response to emerging viral pathogens. Metagenomic techniques can nonspecifically sequence all detectable nucleic acids in a sample and therefore do not rely on prior knowledge of a pathogen's genome. While this technology has been reviewed for bacterial diagnostics and adopted in research settings for the detection and characterization of viruses, viral metagenomics has yet to be widely deployed as a diagnostic tool in clinical laboratories. In this review, we highlight recent improvements to the performance of metagenomic viral sequencing, the current applications of metagenomic sequencing in clinical laboratories, as well as the challenges that impede the widespread adoption of this technology.

Assembling Quality Genomes of Flax Fungal Pathogens from Oxford Nanopore Technologies Data.

Flax (Linum usitatissimum L.) is attacked by numerous devastating fungal pathogens, including Colletotrichum lini, Aureobasidium pullulans, and Fusarium verticillioides (Fusarium moniliforme). The effective control of flax diseases follows the paradigm of extensive molecular research on pathogenicity. However, such studies require quality genome sequences of the studied organisms. This article reports on the approaches to assembling a high-quality fungal genome from the Oxford Nanopore Technologies data. We sequenced the genomes of C. lini, A. pullulans, and F. verticillioides (F. moniliforme) and received different volumes of sequencing data: 1.7 Gb, 3.9 Gb, and 11.1 Gb, respectively. To obtain the optimal genome sequences, we studied the effect of input data quality and genome coverage on assembly statistics and tested the performance of different assembling and polishing software. For C. lini, the most contiguous and complete assembly was obtained by the Flye assembler and the Homopolish polisher. The genome coverage had more effect than data quality on assembly statistics, likely due to the relatively low amount of sequencing data obtained for C. lini. The final assembly was 53.4 Mb long and 96.4% complete (according to the glomerellales_odb10 BUSCO dataset), consisted of 42 contigs, and had an N50 of 4.4 Mb. For A. pullulans and F. verticillioides (F. moniliforme), the best assemblies were produced by Canu-Medaka and Canu-Homopolish, respectively. The final assembly of A. pullulans had a length of 29.5 Mb, 99.4% completeness (dothideomycetes_odb10), an N50 of 2.4 Mb and consisted of 32 contigs. F. verticillioides (F. moniliforme) assembly was 44.1 Mb long, 97.8% complete (hypocreales_odb10), consisted of 54 contigs, and had an N50 of 4.4 Mb. The obtained results can serve as a guideline for assembling a de novo genome of a fungus. In addition, our data can be used in genomic studies of fungal pathogens or plant-pathogen interactions and assist in the management of flax diseases.

From Pathogens to Cancer: Are Cancer Cells Evolved Mitochondrial Super Cells?

Life is based on a highly specific combination of atoms, metabolism, and genetics which eventually reflects the chemistry of the Universe which is composed of hydrogen, oxygen, nitrogen, sulfur, phosphorus, and carbon. The interaction of atomic, metabolic, and genetic cycles results in the organization and de-organization of chemical information of that which we consider as living entities, including cancer cells. In order to approach the problem of the origin of cancer it is therefore reasonable to start from the assumption that the sub-molecular level, the atomic structure, should be the considered starting point on which metabolism, genetics, and external insults eventually emanate. Second, it is crucial to characterize which of the entities and parts composing human cells may live a separate life; certainly, this theoretical standpoint would consider mitochondria, an organelle of "bacteria" origin embedded in conditions favorable for the onset of both. This organelle has not only been tolerated by immunity but has also been placed as a central regulator of cell defense. Virus, bacteria, and mitochondria are also similar in the light of genetic and metabolic elements; they share not only equivalent DNA and RNA features but also many basic biological activities. Thus, it is important to finalize that once the cellular integrity has been constantly broken down, the mitochondria like any other virus or bacteria return to their original autonomy to simply survive. The Warburg's law that states the ability of cancers to ferment glucose in the presence of oxygen, indicates mitochondria respiration abnormalities may be the underlying cause of this transformation towards super cancer cells. Though genetic events play a key part in altering biochemical metabolism, inducing aerobic glycolysis, this is not enough to impair mitochondrial function since mitochondrial biogenesis and quality control are constantly upregulated in cancers. While some cancers have mutations in the nuclear-encoded mitochondrial tricarboxylic acid (TCA) cycle, enzymes that produce oncogenic metabolites, there is also a bio-physic pathway for pathogenic mitochondrial genome mutations. The atomic level of all biological activities can be considered the very beginning, marked by the electron abnormal behavior that consequently affects DNA of both cells and mitochondria. Whilst the cell's nucleus DNA after a certain number of errors and defection tends to gradually switch off, the mitochondria DNA starts adopting several escape strategies, switching-on a few important genes that belong back at their original roots as independent beings. The ability to adopt this survival trick, by becoming completely immune to current life-threatening events, is probably the beginning of a differentiation process towards a "super-power cell", the cancer cells that remind many pathogens, including virus, bacteria, and fungi. Thus, here, we present a hypothesis regarding those changes that first begin at the mitochondria atomic level to steadily involve molecular, tissue and organ levels in response to the virus or bacteria constant insults that drive a mitochondria itself to become an "immortal cancer cell". Improved insights into this interplay between these pathogens and mitochondria progression may disclose newly epistemological paradigms as well as innovative procedures in targeting cancer cell progressive invasion.

Advances in the Microbiological Diagnosis of Prosthetic Joint Infections

A significant number of prosthetic joint infections (PJI) are culture-negative and/or misinterpreted as aseptic failures in spite of the correct implementation of diagnostic culture techniques, such as tissue sample processing in a bead mill, prolonged incubation time, or sonication of removed implants. Misinterpretation may lead to unnecessary surgery and needless antimicrobial treatment. The diagnostic value of non-culture techniques has been investigated in synovial fluid, periprosthetic tissues, and sonication fluid. Different feasible improvements, such as real-time technology, automated systems and commercial kits are now available to support microbiologists. In this review, we describe non-culture techniques based on nucleic acid amplification and sequencing methods. Polymerase chain reaction (PCR) is a frequently used technique in most microbiology laboratories which allows the detection of a nucleic acid fragment by sequence amplification. Different PCR types can be used to diagnose PJI, each one requiring the selection of appropriate primers. Henceforward, thanks to the reduced cost of sequencing and the availability of next-generation sequencing (NGS), it will be possible to identify the whole pathogen genome sequence and, additionally, to detect all the pathogen sequences present in the joint. Although these new techniques have proved helpful, strict conditions need to be observed in order to detect fastidious microorganisms and rule out contaminants. Specialized microbiologists should assist clinicians in interpreting the result of the analyses at interdisciplinary meetings. New technologies will gradually be made available to improve the etiologic diagnoses of PJI, which will remain an important cornerstone of treatment. Strong collaboration among all specialists involved is essential for the correct diagnosis of PJI.

Host heterogeneity and epistasis explain punctuated evolution of SARS-CoV-2.

Identifying drivers of viral diversity is key to understanding the evolutionary as well as epidemiological dynamics of the COVID-19 pandemic. Using rich viral genomic data sets, we show that periods of steadily rising diversity have been punctuated by sudden, enormous increases followed by similarly abrupt collapses of diversity. We introduce a mechanistic model of saltational evolution with epistasis and demonstrate that these features parsimoniously account for the observed temporal dynamics of inter-genomic diversity. Our results provide support for recent proposals that saltational evolution may be a signature feature of SARS-CoV-2, allowing the pathogen to more readily evolve highly transmissible variants. These findings lend theoretical support to a heightened awareness of biological contexts where increased diversification may occur. They also underline the power of pathogen genomics and other surveillance streams in clarifying the phylodynamics of emerging and endemic infections. In public health terms, our results further underline the importance of equitable distribution of up-to-date vaccines.

Recent transposable element bursts are associated with the proximity to genes in a fungal plant pathogen.

The activity of transposable elements (TEs) contributes significantly to pathogen genome evolution. TEs often destabilize genome integrity but may also confer adaptive variation in pathogenicity or resistance traits. De-repression of epigenetically silenced TEs often initiates bursts of transposition activity that may be counteracted by purifying selection and genome defenses. However, how these forces interact to determine the expansion routes of TEs within a pathogen species remains largely unknown. Here, we analyzed a set of 19 telomere-to-telomere genomes of the fungal wheat pathogen Zymoseptoria tritici. Phylogenetic reconstruction and ancestral state estimates of individual TE families revealed that TEs have undergone distinct activation and repression periods resulting in highly uneven copy numbers between genomes of the same species. Most TEs are clustered in gene poor niches, indicating strong purifying selection against insertions near coding sequences, or as a consequence of insertion site preferences. TE families with high copy numbers have low sequence divergence and strong signatures of defense mechanisms (i.e., RIP). In contrast, small non-autonomous TEs (i.e., MITEs) are less impacted by defense mechanisms and are often located in close proximity to genes. Individual TE families have experienced multiple distinct burst events that generated many nearly identical copies. We found that a Copia element burst was initiated from recent copies inserted substantially closer to genes compared to older copies. Overall, TE bursts tended to initiate from copies in GC-rich niches that escaped inactivation by genomic defenses. Our work shows how specific genomic environments features provide triggers for TE proliferation in pathogen genomes.

How public health authorities can use pathogen genomics in health protection practice: a consensus-building Delphi study conducted in the United Kingdom.

Pathogen sequencing guided understanding of SARS-CoV-2 evolution during the COVID-19 pandemic. Many health systems developed pathogen genomics services to monitor SARS-CoV-2. There are no agreed guidelines about how pathogen genomic information should be used in public health practice. We undertook a modified Delphi study in three rounds to develop expert consensus statements about how genomic information should be used. Our aim was to inform health protection policy, planning and practice. Participants were from organisations that produced or used pathogen genomics information in the United Kingdom. The first round posed questions derived from a rapid literature review. Responses informed statements for the subsequent rounds. Consensus was accepted when 70 % or more of the responses were strongly agree/agree, or 70 % were disagree/strongly disagree on the five-point Likert scale. Consensus was achieved in 26 (96 %) of 27 statements. We grouped the statements into six categories: monitoring the emergence of new variants; understanding the epidemiological context of genomic data; using genomic data in outbreak risk assessment and risk management; prioritising the use of limited sequencing capacity; sequencing service performance; and sequencing service capability. The expert consensus statements will help guide public health authorities and policymakers to integrate pathogen genomics in health protection practice.

The DataHarmonizer: a tool for faster data harmonization, validation, aggregation and analysis of pathogen genomics contextual information.

Pathogen genomics is a critical tool for public health surveillance, infection control, outbreak investigations as well as research. In order to make use of pathogen genomics data, they must be interpreted using contextual data (metadata). Contextual data include sample metadata, laboratory methods, patient demographics, clinical outcomes and epidemiological information. However, the variability in how contextual information is captured by different authorities and how it is encoded in different databases poses challenges for data interpretation, integration and their use/re-use. The DataHarmonizer is a template-driven spreadsheet application for harmonizing, validating and transforming genomics contextual data into submission-ready formats for public or private repositories. The tool's web browser-based JavaScript environment enables validation and its offline functionality and local installation increases data security. The DataHarmonizer was developed to address the data sharing needs that arose during the COVID-19 pandemic, and was used by members of the Canadian COVID Genomics Network (CanCOGeN) to harmonize SARS-CoV-2 contextual data for national surveillance and for public repository submission. In order to support coordination of international surveillance efforts, we have partnered with the Public Health Alliance for Genomic Epidemiology to also provide a template conforming to its SARS-CoV-2 contextual data specification for use worldwide. Templates are also being developed for One Health and foodborne pathogens. Overall, the DataHarmonizer tool improves the effectiveness and fidelity of contextual data capture as well as its subsequent usability. Harmonization of contextual information across authorities, platforms and systems globally improves interoperability and reusability of data for concerted public health and research initiatives to fight the current pandemic and future public health emergencies. While initially developed for the COVID-19 pandemic, its expansion to other data management applications and pathogens is already underway.

End-to-end sequence-structure-function meta-learning predicts genome-wide chemical-protein interactions for dark proteins.

Systematically discovering protein-ligand interactions across the entire human and pathogen genomes is critical in chemical genomics, protein function prediction, drug discovery, and many other areas. However, more than 90% of gene families remain "dark"-i.e., their small-molecule ligands are undiscovered due to experimental limitations or human/historical biases. Existing computational approaches typically fail when the dark protein differs from those with known ligands. To address this challenge, we have developed a deep learning framework, called PortalCG, which consists of four novel components: (i) a 3-dimensional ligand binding site enhanced sequence pre-training strategy to encode the evolutionary links between ligand-binding sites across gene families; (ii) an end-to-end pretraining-fine-tuning strategy to reduce the impact of inaccuracy of predicted structures on function predictions by recognizing the sequence-structure-function paradigm; (iii) a new out-of-cluster meta-learning algorithm that extracts and accumulates information learned from predicting ligands of distinct gene families (meta-data) and applies the meta-data to a dark gene family; and (iv) a stress model selection step, using different gene families in the test data from those in the training and development data sets to facilitate model deployment in a real-world scenario. In extensive and rigorous benchmark experiments, PortalCG considerably outperformed state-of-the-art techniques of machine learning and protein-ligand docking when applied to dark gene families, and demonstrated its generalization power for target identifications and compound screenings under out-of-distribution (OOD) scenarios. Furthermore, in an external validation for the multi-target compound screening, the performance of PortalCG surpassed the rational design from medicinal chemists. Our results also suggest that a differentiable sequence-structure-function deep learning framework, where protein structural information serves as an intermediate layer, could be superior to conventional methodology where predicted protein structures were used for the compound screening. We applied PortalCG to two case studies to exemplify its potential in drug discovery: designing selective dual-antagonists of dopamine receptors for the treatment of opioid use disorder (OUD), and illuminating the understudied human genome for target diseases that do not yet have effective and safe therapeutics. Our results suggested that PortalCG is a viable solution to the OOD problem in exploring understudied regions of protein functional space.

Ancient pathogens provide a window into health and well-being

This perspective draws on the record of ancient pathogen genomes and microbiomes illuminating patterns of infectious disease over the course of the Holocene in order to address the following question. How did major changes in living circumstances involving the transition to and intensification of farming alter pathogens and their distributions? Answers to this question via ancient DNA research provide a rapidly expanding picture of pathogen evolution and in concert with archaeological and historical data, give a temporal and behavioral context for heath in the past that is relevant for challenges facing the world today, including the rise of novel pathogens.

Machine learning enables prediction of metabolic system evolution in bacteria.

Evolution prediction is a long-standing goal in evolutionary biology, with potential impacts on strategic pathogen control, genome engineering, and synthetic biology. While laboratory evolution studies have shown the predictability of short-term and sequence-level evolution, that of long-term and system-level evolution has not been systematically examined. Here, we show that the gene content evolution of metabolic systems is generally predictable by applying ancestral gene content reconstruction and machine learning techniques to ~3000 bacterial genomes. Our framework, Evodictor, successfully predicted gene gain and loss evolution at the branches of the reference phylogenetic tree, suggesting that evolutionary pressures and constraints on metabolic systems are universally shared. Investigation of pathway architectures and meta-analysis of metagenomic datasets confirmed that these evolutionary patterns have physiological and ecological bases as functional dependencies among metabolic reactions and bacterial habitat changes. Last, pan-genomic analysis of intraspecies gene content variations proved that even "ongoing" evolution in extant bacterial species is predictable in our framework.

G2GSnake: a Snakemake workflow for host-pathogen genomic association studies.

Joint analyses of paired host and pathogen genome sequences have the potential to enhance our understanding of host-pathogen interactions. A systematic approach to conduct such a joint analysis is through a "genome-to-genome" (G2G) association study, which involves testing for associations between all host and pathogen genetic variants. Significant associations reveal host genetic factors that might drive pathogen variation, highlighting biological mechanisms likely to be involved in host control and pathogen escape. Here, we present a Snakemake workflow that allows researchers to conduct G2G studies in a reproducible and scalable manner. In addition, we have developed an intuitive R Shiny application that generates custom summaries of the results, enabling users to derive relevant insights. G2GSnake is freely available at: https://github.com/zmx21/G2GSnake under the MIT license.

High-Quality Genome Resource of Gilbertella persicaria Causing Peach Soft Rot.

Peach soft rot caused by Gilbertella persicaria is an economically important disease. Here, we report a high-quality complete and annotated genome sequence of G. persicaria strain TFLB-J, isolated from peach fruit in Yuanyang county of Henan Province, China. The assembly consists of 91 scaffolds with an estimated genome size of 33.59 Mb and N50 length of 0.92 Mb, encoding 13,296 predicted protein-coding genes. The whole-genome sequence could provide gene resources for further study of pathogenic effectors and comparative genomics of peach soft rot pathogens.

RNA-Seq Data Processing in Plant-Pathogen Interaction System: A Case Study.

In RNA-seq data processing, short reads are usually aligned from one species against its own genome sequence; however, in plant-pathogen interaction systems, reads from both host and pathogen samples are blended together. In contrast with single-genome analyses, both pathogen and host reference genomes are involved in the alignment process. In such circumstances, the order in which the alignment is carried out, whether the host or pathogen is aligned first, or if both genomes are aligned simultaneously, influences the read counts of certain genes. This is a problem, especially at advanced infection stages. It is crucial to have an appropriate strategy for aligning the reads to their respective genomes, yet the existing strategies of either sequential or parallel alignment become problematic when mapping mixed reads to their corresponding reference genomes. The challenge lies in the determination of which reads belong to which species, especially when homology exists between the host and pathogen genomes. This chapter proposes a combo-genome alignment strategy, which was compared with existing alignment scenarios. Simulation results demonstrated that the degree of discrepancy in the results is correlated with phylogenetic distance of the two species in the mixture which was attributable to the extent of homology between the two genomes involved. This correlation was also found in the analysis using two real RNA-seq datasets of Fusarium-challenged wheat plants. Comparisons of the three RNA-seq processing strategies on three simulation datasets and two real Fusarium-infected wheat datasets showed that an alignment to a combo-genome, consisting of both host and pathogen genomes, improves mapping quality as compared to sequential alignment procedures.

ДИАГНОСТИКА И АДИТИВНАЯ ТЕРАПИЯ МИКОПЛАЗМОЗА МЕЛКОГО РОГАТОГО СКОТА

The aim of the study was to test the complex drug entrikima, which includes: enrofloxacin, trimethoprim and tilmicosin phosphate, on lambs and goats, in farms with mycoplasmosis problems. Before the start of the drug testing, 3 samples from each animal species (6 in total) were taken from diseased lambs and goats in the form of a smear from the nasal passages (during life), as well as after their death from the lungs and articular fluid. Bacteriological studies of a nasal smear isolated P. multocida isolates from 6 samples in 6, and S. isolates were found in 3 samples. sp. hamolisierend, in 2 samples of isolates P. haemolytica and M. mycoides subsp. mycoides. When examining the light corpses of fallen lambs and goats, 3 samples were also taken from each animal species. At the same time, P. multocida isolates were isolated from 6 samples in 6, S. isolates were found in 4 samples. sp. hamolisierend, in 3 samples of P. isolates. haemolytica and M. agalactiae and in 2 M. mycoides subsp. mycoides. In the study of articular fluid from the corpses of fallen lambs and goats, 3 samples were also taken from each animal species. At the same time, isolates were isolated in 6 samples out of 6. - S. sp. hamolisierend, isolates were found in 4 samples: P. haemolytica, M. agalactiae и M. mycoides subsp. mycoides. To confirm the diagnosis obtained by bacteriological studies, a molecular genetic diagnostic method (PCR) was also used. In PCR, the results obtained during bacteriological studies of the lungs were confirmed. The genomes of pathogens: M. mycoides subsp. mycoides, M. agalactiae P. haemolytica and S. sp. hamolisierend were detected in all 6 samples. For the treatment of lambs and goats, a 5% solution of entrikim was used orally at a dose of 0.5 cm3 / 1 kg of body weight twice a day for 7 consecutive days. 3 days after the end of the course of treatment, a nasal smear was taken for complex laboratory studies (bacteriological and molecular genetic). PCR studies have established that the applied therapy did not fully have a positive effect on the release of the organism of young cattle from certain types of mycoplasmas, in particular, the M. agalactiae genome was detected in one sample out of six (16.6%), as well as in two samples out of six genomes of P. multocida and S. sp. Hamolisierend (33.3%).