Genome Sequences Of Pathogens Research Articles

Reverse vaccinology: A strategy also used for identifying potential vaccine antigens in poultry.

Vaccination of livestock plays a major role in improving animal health, welfare and productivity, but also in public health by preventing zoonotic diseases. Advances in bioinformatics and whole-genome sequencing techniques since the 2000s have led to the development of genome-based vaccinology, called reverse vaccinology. Reverse vaccinology is a rapid and competitive strategy that uses pathogen genome sequences to screen for and identify potential vaccine antigens and, unlike conventional methods, does not require culturing the pathogenic microorganism, at least initially. Based on in silico approaches and dedicated software, reverse vaccinology has led to the identification of a wide range of proteins as putative vaccine candidates against human pathogens and has been applied more recently to several animal diseases. After a brief overview of the principle of the approach and its applications in human medicine, this review focuses on the use of reverse vaccinology for the development of vaccines specifically for poultry, a representative example of livestock vaccination, and discusses the important points to consider when using this method.

Trends and impacts of SARS-CoV-2 genome sharing: a comparative analysis of China and the global community, 2020-2023.

The global sharing of pathogen genome sequences has been significantly expedited by the COVID-19 pandemic. This study aims to elucidate the global landscape of SARS-CoV-2 genome sharing between 2020 and 2023 with a focus on quantity, timeliness, and quality. Specifically, the characteristics of China are examined. SARS-CoV-2 genomes along with associated metadata were sourced from GISAID database. The genomes were analyzed to evaluate the quantity, timeliness, and quality across different countries/regions. The metadata characteristics of shared genomes in China in 2023 were examined and compared with the actual demographic data of China in 2023. From 2020 to 2023, European countries consistently maintained high levels of genomic data sharing in terms of quantity, timeliness, and quality. In 2023, China made remarkable improvements in sequence sharing, ranking among the top 3.89% globally for quantity, 22.78% for timeliness, and 17.78% for quality. The genome sharing in China in 2023 covered all provinces with Shanghai Municipality contributing the most genomes. Human samples accounted for 99.73% of the shared genomes and exhibited three distinct peaks in collection dates. Males constituted 52.06%, while females constituted 47.94%. Notably, there was an increase in individuals aged 65 and above within the GISAID database compared to China's overall population in 2023. The global sharing of SARS-CoV-2 genomes in 2020-2023 exhibited disparities in terms of quantity, timeliness, and quality. However, China has made significant advancements since 2023 by achieving comprehensive coverage across provinces, timely dissemination of data, and widespread population monitoring. Strengthening data sharing capabilities in countries like China during the SARS-CoV-2 pandemic will play a crucial role in containing and responding to future pandemics caused by emerging pathogens.

A-238 Lyophilized Bead Multiplex Assays for CT/NG/TV Detection

Abstract Background Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and Trichomonas vaginalis (TV) cause the three most prevalent sexually transmitted infectious diseases in developed countries, contributing to approximately 300 million new infections worldwide, annually. Due to the challenges of culturing and using immunoassays to detect these pathogens, DNA-based molecular tests have been instrumental, and current trends in molecular testing for CT/NG/TV have moved toward point-of-care tests. Lyophilization provides benefits required for point-of-care tests, such as ambient storage, extended shelf life, simplified downstream workflow, and variable formats. A lyophilized-bead format enables an assay to be placed in sealed consumables and stored at room temperature for up to two years. An additional consideration is the need for endogenous and exogenous controls. Exogenous in-process controls can be used to validate the performance of workflows culminating in a qPCR reaction and provide flexibility to test developers. An ideal exogenous in-process control is nonhomologous to human or human pathogen genome sequences and does not align with primers or probes designed for pathogen detection. The objective of the current study was to develop a lyophilized-bead-format assay containing an ideal exogenous control and establish whether it is a valid option for the accurate detection of CT, NG, and TV. Methods A synthetic DNA control containing targets for CT/NG/TV/RNase P (RP)/exogenous control was used to establish an analytical LOD by qPCR. The 5-plex assay, lyophilized in beads, was hydrated and tested for linearity over an 8-log range of the synthetic DNA control. Further, the qPCR lyophilized bead with assay was tested with a proficiency sample by extracting DNA from ZeptoMetrix NATtrol CT/NG/TV Positive Control and spiking-in the exogenous DNA control. qPCR was performed on the extracted DNA and human cDNA. Results The analytical LOD for the control DNA was determined to be 5 copies/reaction. Additionally, linearity was observed by qPCR over an 8-log range of the synthetic DNA control for all five targets in multiplex with good efficiencies and R2 values. Finally, all targets were amplified and detected by qPCR using DNA extracted from ZeptoMetrix NATtrol CT/NG/TV Positive Control with spiked-in exogenous DNA control. The detection of the exogenous sequence in the qPCR multiplex reaction indicated the extraction was successful. Conclusions We have developed a multiplex qPCR assay in lyophilized-bead format that can identify infectious agents, such as CT/NG/TV, in a single reaction. We have included RP as a human host control, plus an exogenous in-process control, for a total of 5-plex in separate fluorescent channels. We have shown that our lyophilized beads with assay produce a positive qPCR result when combined with a proficiency sample.

Identification of specific genes as molecular markers for rapid and accurate detection of oil-tea Camellia anthracnose pathogen Colletotrichum fructicola in China.

Camellia anthracnose is caused by multiple Colletotrichum species, resulting in severe yield losses of oil-tea Camellia. Colletotrichum fructicola is one of the major anthracnose pathogens of oil-tea Camellia worldwide. However, developing unique molecular markers for the rapid and accurate detection of Colletotrichum fructicola from diverse Colletotrichum species, as well as early monitoring and effective control of the disease, remains largely unexplored. C. fructicola-specific genes were obtained using a BLAST search of the sequences of predicted genes in C. fructicola against the genome sequences of Colletotrichum fungal pathogens. In this study, Colletotrichum fructicola-specific molecular markers were developed for rapid and accurate detection of C. fructicola among Camellia anthracnose causing fungal pathogens. Using genomic DNA-based end-point PCR and qPCR, three C. fructicola-specific genes with the ability to distinguish C. fructicola from other oil-tea Camellia anthracnose-related Colletotrichum species, including Colletotrichum camelliae, Colletotrichum gloeosporioides, and Colletotrichum siamense, and oil-tea Camellia fungal pathogens belonging to the genus Neopestalotiopsis, Pestalotiopsis, and Alternaria, were validated as molecular markers. In addition, these three molecular markers were highly sensitive to detecting C. fructicola using DNA extracted from the inoculated leaves of oil-tea Camellia. These findings enable us to rapidly and uniquely detect the Camellia anthracnose disease caused by Colletotrichum fructicola, which will equip farmers with an effective tool for monitoring Camellia anthracnose disease in the field and taking timely control measurements in advance.

A secure visualization platform for pathogenic genome analysis with an accurate reference database

A secure visualization platform for pathogenic genome analysis with an accurate reference database

Ecological and evolutionary mechanisms driving within-patient emergence of antimicrobial resistance.

The ecological and evolutionary mechanisms of antimicrobial resistance (AMR) emergence within patients and how these vary across bacterial infections are poorly understood. Increasingly widespread use of pathogen genome sequencing in the clinic enables a deeper understanding of these processes. In this Review, we explore the clinical evidence to support four major mechanisms of within-patient AMR emergence in bacteria: spontaneous resistance mutations; in situ horizontal gene transfer of resistance genes; selection of pre-existing resistance; and immigration of resistant lineages. Within-patient AMR emergence occurs across a wide range of host niches and bacterial species, but the importance of each mechanism varies between bacterial species and infection sites within the body. We identify potential drivers of such differences and discuss how ecological and evolutionary analysis could be embedded within clinical trials of antimicrobials, which are powerful but underused tools for understanding why these mechanisms vary between pathogens, infections and individuals. Ultimately, improving understanding of how host niche, bacterial species and antibiotic mode of action combine to govern the ecological and evolutionary mechanism of AMR emergence in patients will enable more predictive and personalized diagnosis and antimicrobial therapies.

Comprehensive genetic analysis of the first near-complete genome of bovine coronavirus and partial genome of bovine rotavirus in Türkiye through metagenomics.

Obtaining the complete or near-complete genome sequence of pathogens is becoming increasingly crucial for epidemiology, virology, clinical science and practice. This study aimed to detect viruses and conduct genetic characterization of genomes using metagenomics in order to identify the viral agents responsible for a calf's diarrhoea. The findings showed that bovine coronavirus (BCoV) and bovine rotavirus (BRV) are the primary viral agents responsible for the calf's diarrhoea. The current study successfully obtained the first-ever near-complete genome sequence of a bovine coronavirus (BCoV) from Türkiye. The G+C content was 36.31% and the genetic analysis revealed that the Turkish BCoV strain is closely related to respiratory BCoV strains from France and Ireland, with high nucleotide sequence and amino acid identity and similarity. In the present study, analysis of the S protein of the Turkish BCoV strain revealed the presence of 13 amino acid insertions, one of which was found to be shared with the French respiratory BCoV. The study also identified a BRV strain through metagenomic analysis and detected multiple mutations within the structural and non-structural proteins of the BRV strain, suggesting that the BRV Kirikkale strain may serve as an ancestor for reassortants with interspecies transmission, especially involving rotaviruses that infect rabbits and giraffes.

Challenges to Precision Public Health in Nigeria

With the waves of evolution in genomics and genomics technology, the 21st century has experienced a surge in human and pathogen genome sequencing both at the clinical and public health care levels. These latest efforts have led to what is commonly referred to as "precision public health," which is a multidisciplinary field that incorporates genomics, artificial intelligence (AI), and big data to help predict the healthcare outcomes of an individual and improve the general population's health. To individualize healthcare at the clinical and public health levels, research efforts have seen the emergence and utilization of technology in the management of healthcare. Despite precision public health being ascribed as a highly promising tool that could help provide solutions to many public health problems in developed societies, how this turns out in developing nations is yet to be established. This study applied an analytical cross-sectional study design and aimed at assessing challenges and enablers of PPH in Nigeria using genomic surveillance with an objective of understanding the challenges, establishing the influence of data integration methods on the attainment of PPH, the influence of health equity on the attainment of PPH and identifying the influence of health policies. The empirical literature review and cross-sectional study design were used with SPSS 23, and the visualization of data was done using the Microsoft Excel 2019 software. The study findings illustrated that more than 52% of the respondents have heard about precision public health, with 56.4% of the respondents disagreeing with the equitable distribution of technological infrastructure to support data management. A high proportion of the respondents agree that the government can implement PPH in Nigeria. However, a slightly higher proportion of the respondents (46.2%) disagreed on the role of the private sector in establishing PPH across private health facilities and the need for political goodwill to support the implementation of PPH in Nigeria. In conclusion, PPH can help improve disease prevention strategies, treatment, and control efforts if appropriately implemented, and the study recommends a need for African studies to aggregate, analyze, visualize, and make available high quality for PPH to be more effective than traditional public health.

Inference of Infectious Disease Transmission through a Relaxed Bottleneck Using Multiple Genomes Per Host.

In recent times, pathogen genome sequencing has become increasingly used to investigate infectious disease outbreaks. When genomic data is sampled densely enough amongst infected individuals, it can help resolve who infected whom. However, transmission analysis cannot rely solely on a phylogeny of the genomes but must account for the within-host evolution of the pathogen, which blurs the relationship between phylogenetic and transmission trees. When only a single genome is sampled for each host, the uncertainty about who infected whom can be quite high. Consequently, transmission analysis based on multiple genomes of the same pathogen per host has a clear potential for delivering more precise results, even though it is more laborious to achieve. Here, we present a new methodology that can use any number of genomes sampled from a set of individuals to reconstruct their transmission network. Furthermore, we remove the need for the assumption of a complete transmission bottleneck. We use simulated data to show that our method becomes more accurate as more genomes per host are provided, and that it can infer key infectious disease parameters such as the size of the transmission bottleneck, within-host growth rate, basic reproduction number, and sampling fraction. We demonstrate the usefulness of our method in applications to real datasets from an outbreak of Pseudomonas aeruginosa amongst cystic fibrosis patients and a nosocomial outbreak of Klebsiella pneumoniae.

Genetic diversity and phylogenetic analyses of Asian lineage Zika virus whole genome sequences derived from Culex quinquefasciatus mosquitoes and urine of patients during the 2020 epidemic in Thailand

Zika virus (ZIKV), a mosquito-borne flavivirus, has been continually emerging and re-emerging since 2010, with sporadic cases reported annually in Thailand, peaking at over 1000 confirmed positive cases in 2016. Leveraging high-throughput sequencing technologies, specifically whole genome sequencing (WGS), has facilitated rapid pathogen genome sequencing. In this study, we used multiplex amplicon sequencing on the Illumina Miseq instrument to describe ZIKV WGS. Six ZIKV WGS were derived from three samples of field-caught Culex quinquefasciatus mosquitoes (two males and one female) and three urine samples collected from patients in three different provinces of Thailand. Additionally, successful isolation of a ZIKV isolate occurred from a female Cx. quinquefasciatus. The WGS analysis revealed a correlation between the 2020 outbreak and the acquisition of five amino acid changes in the Asian lineage ZIKV strains from Thailand (2006), Cambodia (2010 and 2019), and the Philippines (2012). These changes, including C-T106A, prM-V1A, E-V473M, NS1-A188V, and NS5-M872V, were identified in all seven WGS, previously linked to significantly higher mortality rates. Furthermore, phylogenetic analysis indicated that the seven ZIKV sequences belonged to the Asian lineage. Notably, the genomic region of the E gene showed the highest nucleotide diversity (0.7–1.3%). This data holds significance in informing the development of molecular tools that enhance our understanding of virus patterns and evolution. Moreover, it may identify targets for improved methods to prevent and control future ZIKV outbreaks.

B-148 Analytical Validation and Performance Characteristics of A Targeted Metagenomics Next-generation Sequencing Respiratory Pathogen ID/AMR Panel

Abstract Background The COVID-19 global pandemic underscored the importance of access to diagnostic testing, broad community surveillance, and genomic analysis of pathogen variants. The dearth of testing in the initial days and months of the pandemic highlighted the need to improve public health infrastructure. The subsequent onset of viral evolution, producing new and functionally different CoV2 strains, increased the importance for the availability and scalability of pathogen genome sequencing and data sharing pipelines through national surveillance programs. As SARS-CoV-2 moves from a pandemic to endemic state, the scientific and medical community must not forget the lessons learned and continue to reinforce the value of ongoing monitoring of circulating pathogens. Methods Aegis Sciences performed an analytical validation of the Respiratory Pathogen ID/AMR Target Enrichment Panel (RPIP, Illumina RUO), a next-generation sequencing assay that uses target capture-based enrichment for detection, quantification, and characterization of 282 viral, bacterial, and fungal respiratory pathogens and over 2000 antimicrobial resistance (AMR) genes. A total of 1598 validation samples were sequenced via the NextSeq 550 Dx (Illumina) and demultiplexed and assembled FASTQ files were analyzed with Explify RPIP Analysis application in BaseSpace Sequencing Hub (Illumina). Samples tested were contrived specimens using 60 different pathogen isolates various concentrations and clinical comparative samples, and the study included the evaluation of concentration vs genome coverage, inclusivity, exclusivity, and orthogonal analyses. Results RPIP is a highly sensitive, robust sequencing assay that can detect organisms at very low concentrations. Evaluation of copy number vs genome coverage revealed that 53 out of 60 organisms were detected at 1 copy/µL (PPV = 86.67%), and 60 out of 60 were detected at 10 copies/µL (PPV = 98.33%) and 50 copies/µL (PPV = 96.67%). The average coverage across the genome improved with increasing concentration and was 59.97% at 1 copy/µL, 72.45% at 10 copies/µL, and >90% at 50 copies/µL. Inclusivity and exclusivity studies revealed an increase in false positives at low concentrations (1 copy/µL = 35.11%) and a reduction of false positives at higher concentrations (10 copies/µL = 20.3%) of isolates, and higher copy numbers of isolates allow for the true positives to be distinguished from contaminants and off-target organisms with very low coverage and quantification results. Orthogonal studies with upper respiratory clinical specimens tested previously by validated PCR methods revealed the following performance characteristics for respiratory pathogens, including SARS-CoV-2, influenza, parainfluenza, and rhinovirus: PPV = 81.11%, NPV = 99.66%, Sensitivity = 98.46%, and Specificity = 93.89%. Conclusions Completion of these studies demonstrated that next-generation sequencing is a cost effective, high-throughput option for broad pathogen tracking and surveillance. Laboratories, like Aegis, must continue to leverage collaborative relationships with public and private sector entities to expand resources, foster innovation, and broaden capabilities to quickly respond to biological threats.

Viral genetic clustering and transmission dynamics of the 2022 mpox outbreak in Portugal

Pathogen genome sequencing during epidemics enhances our ability to identify and understand suspected clusters and investigate their relationships. Here, we combine genomic and epidemiological data of the 2022 mpox outbreak to better understand early viral spread, diversification and transmission dynamics. By sequencing 52% of the confirmed cases in Portugal, we identified the mpox virus sublineages with the highest impact on case numbers and fitted them into a global context, finding evidence that several international sublineages probably emerged or spread early in Portugal. We estimated a 62% infection reporting rate and that 1.3% of the population of men who have sex with men in Portugal were infected. We infer the critical role played by sexual networks and superspreader gatherings, such as sauna attendance, in the dissemination of mpox virus. Overall, our findings highlight genomic epidemiology as a tool for the real-time monitoring and control of mpox epidemics, and can guide future vaccine policy in a highly susceptible population.

Antimicrobial resistance heterogeneity among multidrug-resistant Gram-negative pathogens: Phenotypic, genotypic, and proteomic analysis

Microbes evolve rapidly by modifying their genomes through mutations or through the horizontal acquisition of mobile genetic elements (MGEs) linked with fitness traits such as antimicrobial resistance (AMR), virulence, and metabolic functions. We conducted a multicentric study in India and collected different clinical samples for decoding the genome sequences of bacterial pathogens associated with sepsis, urinary tract infections, and respiratory infections to understand the functional potency associated with AMR and its dynamics. Genomic analysis identified several acquired AMR genes (ARGs) that have a pathogen-specific signature. We observed that blaCTX-M-15, blaCMY-42, blaNDM-5, and aadA(2) were prevalent in Escherichia coli, and blaTEM-1B, blaOXA-232, blaNDM-1, rmtB, and rmtC were dominant in Klebsiella pneumoniae. In contrast, Pseudomonas aeruginosa and Acinetobacter baumannii harbored blaVEB, blaVIM-2, aph(3'), strA/B, blaOXA-23, aph(3') variants, and amrA, respectively. Regardless of the type of ARG, the MGEs linked with ARGs were also pathogen-specific. The sequence type of these pathogens was identified as high-risk international clones, with only a few lineages being predominant and region-specific. Whole-cell proteome analysis of extensively drug-resistant K. pneumoniae, A. baumannii, E. coli, and P. aeruginosa strains revealed differential abundances of resistance-associated proteins in the presence and absence of different classes of antibiotics. The pathogen-specific resistance signatures and differential abundance of AMR-associated proteins identified in this study should add value to AMR diagnostics and the choice of appropriate drug combinations for successful antimicrobial therapy.

Towards a post-pandemic future for global pathogen genome sequencing.

Pathogen genome sequencing has become a routine part of our response to active outbreaks of infectious disease and should be an important part of our preparations for future epidemics. In this Essay, we discuss the innovations that have enabled routine pathogen genome sequencing, as well as how genome sequences can be used to understand and control the spread of infectious disease. We also explore the impact of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic on the field of pathogen genomics and outline the challenges we must address to further improve the utility of pathogen genome sequencing in the future.

Whole genome sequence and diversity in multigene families of Babesia ovis.

Ovine babesiosis, caused by Babesia ovis, is an acute, lethal, and endemic disease worldwide and causes a huge economic loss to animal industry. Pathogen genome sequences can be utilized for selecting diagnostic markers, drug targets, and antigens for vaccine development; however, those for B. ovis have not been available so far. In this study, we obtained a draft genome sequence for B. ovis isolated from an infected sheep in Turkey. The genome size was 7.81 Mbp with 3,419 protein-coding genes. It consisted of 41 contigs, and the N50 was 526 Kbp. There were 259 orthologs identified among eight Babesia spp., Plasmodium falciparum, and Toxoplasma gondii. A phylogeny was estimated on the basis of the orthologs, which showed B. ovis to be closest to B. bovis. There were 43 ves genes identified using hmm model as well. They formed a discriminating cluster to other ves multigene family of Babesia spp. but showed certain similarities to those of B. bovis, B. caballi, and Babesia sp. Xinjiang, which is consistent with the phylogeny. Comparative genomics among B. ovis and B. bovis elucidated uniquely evolved genes in these species, which may account for the adaptation.

Decoding the Fundamental Drivers of Phylodynamic Inference.

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

When Everything Becomes Bigger: Big Data for Big Poultry Production.

In future decades, the demand for poultry meat and eggs is predicted to considerably increase in pace with human population growth. Although this expansion clearly represents a remarkable opportunity for the sector, it conceals a multitude of challenges. Pollution and land erosion, competition for limited resources between animal and human nutrition, animal welfare concerns, limitations on the use of growth promoters and antimicrobial agents, and increasing risks and effects of animal infectious diseases and zoonoses are several topics that have received attention from authorities and the public. The increase in poultry production must be achieved mainly through optimization and increased efficiency. The increasing ability to generate large amounts of data ("big data") is pervasive in both modern society and the farming industry. Information accessibility-coupled with the availability of tools and computational power to store, share, integrate, and analyze data with automatic and flexible algorithms-offers an unprecedented opportunity to develop tools to maximize farm profitability, reduce socio-environmental impacts, and increase animal and human health and welfare. A detailed description of all topics and applications of big data analysis in poultry farming would be infeasible. Therefore, the present work briefly reviews the application of sensor technologies, such as optical, acoustic, and wearable sensors, as well as infrared thermal imaging and optical flow, to poultry farming. The principles and benefits of advanced statistical techniques, such as machine learning and deep learning, and their use in developing effective and reliable classification and prediction models to benefit the farming system, are also discussed. Finally, recent progress in pathogen genome sequencing and analysis is discussed, highlighting practical applications in epidemiological tracking, and reconstruction of microorganisms' population dynamics, evolution, and spread. The benefits of the objective evaluation of the effectiveness of applied control strategies are also considered. Although human-artificial intelligence collaborations in the livestock sector can be frightening because they require farmers and employees in the sector to adapt to new roles, challenges, and competencies-and because several unknowns, limitations, and open-ended questions are inevitable-their overall benefits appear to be far greater than their drawbacks. As more farms and companies connect to technology, artificial intelligence (AI) and sensing technologies will begin to play a greater role in identifying patterns and solutions to pressing problems in modern animal farming, thus providing remarkable production-based and commercial advantages. Moreover, the combination of diverse sources and types of data will also become fundamental for the development of predictive models able to anticipate, rather than merely detect, disease occurrence. The increasing availability of sensors, infrastructures, and tools for big data collection, storage, sharing, and analysis-together with the use of open standards and integration with pathogen molecular epidemiology-have the potential to address the major challenge of producing higher-quality, more healthful food on a larger scale in a more sustainable manner, thereby protecting ecosystems, preserving natural resources, and improving animal and human welfare and health.

Genofunc: genome annotation and identification of genome features for automated pipelining analysis of virus whole genome sequences

BackgroundViral genomics and epidemiology have been increasingly important tools for analysing the spread of key pathogens affecting daily lives of individuals worldwide. With the rapidly expanding scale of pathogen genome sequencing efforts for epidemics and outbreaks efficient workflows in extracting genomic information are becoming increasingly important for answering key research questions.ResultsHere we present Genofunc, a toolkit offering a range of command line orientated functions for processing of raw virus genome sequences into aligned and annotated data ready for analysis. The tool contains functions such as genome annotation, feature extraction etc. for processing of large genomic datasets both manual or as part of pipeline such as Snakemake or Nextflow ready for down-stream phylogenetic analysis. Originally designed for a large-scale HIV sequencing project, Genofunc has been benchmarked against annotated sequence gene coordinates from the Los Alamos HIV database as validation with downstream phylogenetic analysis result comparable to past literature as case study.ConclusionGenofunc is implemented fully in Python and licensed under the MIT license. Source code and documentation is available at: https://github.com/xiaoyu518/genofunc.

Investigating Possible Interspecies Communication of Plasmids Associated with Transfer of Third-Generation Cephalosporin, Quinolone, and Colistin Resistance Between Simultaneously Isolated Escherichia Coli and Klebsiella Pneumoniae.

The coinfection process producing multiple species of pathogens provides a specific ecological niche for the exchange of genetic materials between pathogens, in which plasmids play a vital role in horizontal gene transfer, especially for drug resistance, but the underlying transfer pathway remains unclear. Interspecies communication of the plasmids associated with the transfer of third-generation cephalosporins, quinolones, and colistin resistance has been observed in simultaneously isolated Escherichia coli and Klebsiella pneumoniae from abdominal drainage following surgery. The MICs of antimicrobial agents were determined by the broth microdilution method. The complete chromosome and plasmid sequences were obtained by combining Illumina paired-end short reads and MinION long reads. S1-PFGE, southern blot analysis and conjugation assay confirmed the transferability of the mcr-1-harboring plasmid. Both the E. coli isolate EC15255 and K. pneumoniae isolate KP15255 from the same specimen presented multidrug resistance. Each of them harbored one chromosome and three plasmids, and two plasmids and their mediated resistance could be transferred to the recipient by conjugation. Comparison of their genome sequences suggested that several genetic communication events occurred between species, especially among their plasmids, such as whole-plasmid transfer, insertion, deletion, amplification, or inversion. Exchange of plasmids or the genetic elements they harbor plays a critical role in antimicrobial resistance gene transmission and poses a substantial threat to nosocomial infection control, necessitating the continued surveillance of multidrug resistant pathogens, especially during coinfection. IMPORTANCE The genome sequence of bacterial pathogens commonly provides a detailed clue of genetic communication among clones or even distinct species. The intestinal microecological environment is a representative ecological niche for genetic communication. However, it is still difficult to describe the details of horizontal gene transfer or other genetic events within them because the evidence in the genome sequence is incomplete and limited. In this study, the simultaneously isolated Escherichia coli and Klebsiella pneumoniae from a coinfection process provided an excellent example for observation of interspecies communication between the two genomes and the plasmids they harbor. A complete genome sequence acquired by combining the Illumina and MinION sequencing platforms facilitated the understanding of genetic communication events, such as whole-plasmid transfer, insertion, deletion, amplification, or inversion, which contribute to antimicrobial resistance gene transmission and are a substantial threat to nosocomial infection control.

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.