Clinical detection and characterization of bacterial pathogens in the genomics era

Harnessing technology for infectious disease response in conflict zones: Challenges, innovations, and policy implications

Epidemic outbreaks of infectious diseases in conflict zones are complex threats to public health and humanitarian activities that require creativity approaches of reducing their damage. This narrative review focuses on the technology intersection with infectious disease response in conflict zones, and complexity of healthcare infrastructure, population displacement, and security risks. This narrative review explores how conflict-related destruction is harmful towards healthcare systems and the impediments to disease surveillance and response activities. In this regards, the review also considered the contributions of technological innovations, such as the improvement of epidemiological surveillance, mobile health (mHealth) technologies, genomic sequencing, and surveillance technologies, in strengthening infectious disease management in conflict settings. Ethical issues related to data privacy, security and fairness are also covered. By advisement on policy that focuses on investment in surveillance systems, diagnostic capacity, capacity building, collaboration, and even ethical governance, stakeholders can leverage technology to enhance the response to infectious disease in conflict settings and, thus, protect the global health security. This review is full of information for researchers, policymakers, and practitioners who are dealing with the issues of infectious disease outbreaks in conflicts worn areas.

Emerging strategies and therapeutic innovations for combating drug resistance in Staphylococcus aureus strains: A comprehensive review

In recent years, antibiotic therapy has encountered significant challenges due to the rapid emergence of multidrug resistance among bacteria responsible for life-threatening illnesses, creating uncertainty about the future management of infectious diseases. The escalation of antimicrobial resistance in the post-COVID era compared to the pre-COVID era has raised global concern. The prevalence of nosocomial-related infections, especially outbreaks of drug-resistant strains of Staphylococcus aureus, have been reported worldwide, with India being a notable hotspot for such occurrences. Various virulence factors and mutations characterize nosocomial infections involving S. aureus. The lack of proper alternative treatments leading to increased drug resistance emphasizes the need to investigate and examine recent research to combat future pandemics. In the current genomics era, the application of advanced technologies such as next-generation sequencing (NGS), machine learning (ML), and quantum computing (QC) for genomic analysis and resistance prediction has significantly increased the pace of diagnosing drug-resistant pathogens and insights into genetic intricacies. Despite prompt diagnosis, the elimination of drug-resistant infections remains unattainable in the absence of effective alternative therapies. Researchers are exploring various alternative therapeutic approaches, including phage therapy, antimicrobial peptides, photodynamic therapy, vaccines, host-directed therapies, and more. The proposed review mainly focuses on the resistance journey of S. aureus over the past decade, detailing its resistance mechanisms, prevalence in the subcontinent, innovations in rapid diagnosis of the drug-resistant strains, including the applicants of NGS and ML application along with QC, it helps to design alternative novel therapeutics approaches against S. aureus infection.

Application of next-generation sequencing to identify different pathogens

Early and precise detection and identification of various pathogens are essential for epidemiological monitoring, disease management, and reducing the prevalence of clinical infectious diseases. Traditional pathogen detection techniques, which include mass spectrometry, biochemical tests, molecular testing, and culture-based methods, are limited in application and are time-consuming. Next generation sequencing (NGS) has emerged as an essential technology for identifying pathogens. NGS is a cutting-edge sequencing method with high throughput that can create massive volumes of sequences with a broad application prospects in the field of pathogen identification and diagnosis. In this review, we introduce NGS technology in detail, summarizes the application of NGS in that identification of different pathogens, including bacteria, fungi, and viruses, and analyze the challenges and outlook for using NGS to identify clinical pathogens. Thus, this work provides a theoretical basis for NGS studies and provides evidence to support the application of NGS in distinguishing various clinical pathogens.

Addressing the Knowledge Deficit in Hospital Bed Planning and Defining an Optimum Region for the Number of Different Types of Hospital Beds in an Effective Health Care System

Based upon 30-years of research by the author, a new approach to hospital bed planning and international benchmarking is proposed. The number of hospital beds per 1000 people is commonly used to compare international bed numbers. This method is flawed because it does not consider population age structure or the effect of nearness-to-death on hospital utilization. Deaths are also serving as a proxy for wider bed demand arising from undetected outbreaks of 3000 species of human pathogens. To remedy this problem, a new approach to bed modeling has been developed that plots beds per 1000 deaths against deaths per 1000 population. Lines of equivalence can be drawn on the plot to delineate countries with a higher or lower bed supply. This method is extended to attempt to define the optimum region for bed supply in an effective health care system. England is used as an example of a health system descending into operational chaos due to too few beds and manpower. The former Soviet bloc countries represent a health system overly dependent on hospital beds. Several countries also show evidence of overutilization of hospital beds. The new method is used to define a potential range for bed supply and manpower where the most effective health systems currently reside. The method is applied to total curative beds, medical beds, psychiatric beds, critical care, geriatric care, etc., and can also be used to compare different types of healthcare staff, i.e., nurses, physicians, and surgeons. Issues surrounding the optimum hospital size and the optimum average occupancy will also be discussed. The role of poor policy in the English NHS is used to show how the NHS has been led into a bed crisis. The method is also extended beyond international benchmarking to illustrate how it can be applied at a local or regional level in the process of long-term bed planning. Issues regarding the volatility in hospital admissions are also addressed to explain the need for surge capacity and why an adequate average bed occupancy margin is required for an optimally functioning hospital.

Insights into molecular aspects of pathogenesis and disease management in acute hepatopancreatic necrosis disease (AHPND): An updated review

Shrimp aquaculture is a rapidly growing sector that makes a significant economic contribution. However, the aquaculture industry is confronted with significant challenges, and infectious diseases, notably Acute Hepatopancreatic Necrosis Disease (AHPND), have emerged as severe threat. AHPND is caused by pathogens carrying the pVA-1 plasmid, which expresses the PirAB toxin, and it has wreaked havoc in shrimp aquaculture, imposing substantial economic burdens. To address this issue, it is crucial to delve into shrimp's immune responses. Therefore, this comprehensive review offers an in-depth examination of AHPND outbreaks, encompassing various facets such as environmental factors, host susceptibility, and the mechanisms employed by the pathogens. Traditional approaches to combat AHPND, primarily relying on chemicals and antibiotics, have raised concerns related to antibiotic resistance and have demonstrated limited success in disease control. Hence this review spotlights recent advancements in molecular diagnostics, therapeutic agents, and research related to shrimp immunity. Understanding these developments is crucial in the ongoing battle against AHPND. In conclusion, this review underscores the pressing need to comprehend the underlying mechanisms of AHPND pathogenesis and emphasizes the importance of developing comprehensive and effective solutions to combat this devastating disease, which continues to threaten the sustainability of shrimp farming.

Recent advances in surface enhanced Raman spectroscopy for bacterial pathogen identifications

BACKGROUND

The rapid and reliable detection of pathogenic bacteria at an early stage is a highly significant research field for public health. However, most traditional approaches for pathogen identification are time-consuming and labour-intensive, which may cause physicians making inappropriate treatment decisions based on an incomplete diagnosis of patients with unknown infections, leading to increased morbidity and mortality. Therefore, novel methods are constantly required to face the emerging challenges of bacterial detection and identification. In particular, Raman spectroscopy (RS) is becoming an attractive method for rapid and accurate detection of bacterial pathogens in recent years, among which the newly developed surface-enhanced Raman spectroscopy (SERS) shows the most promising potential.

AIM OF REVIEW

Recent advances in pathogen detection and diagnosis of bacterial infections were discussed with focuses on the development of the SERS approaches and its applications in complex clinical settings.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The current review describes bacterial classification using surface enhanced Raman spectroscopy (SERS) for developing a rapid and more accurate method for the identification of bacterial pathogens in clinical diagnosis. The initial part of this review gives a brief overview of the mechanism of SERS technology and development of the SERS approach to detect bacterial pathogens in complex samples. The development of the label-based and label-free SERS strategies and several novel SERS-compatible technologies in clinical applications, as well as the analytical procedures and examples of chemometric methods for SERS, are introduced. The computational challenges of pre-processing spectra and the highlights of the limitations and perspectives of the SERS technique are also discussed.Taken together, this systematic review provides an overall summary of the SERS technique and its application potential for direct bacterial diagnosis in clinical samples such as blood, urine and sputum, etc.

Metaproteomic Analysis of Nasopharyngeal Swab Samples to Identify Microbial Peptides in COVID-19 Patients

During the COVID-19 pandemic, impaired immunity and medical interventions resulted in cases of secondary infections. The clinical difficulties and dangers associated with secondary infections in patients necessitate the exploration of their microbiome. Metaproteomics is a powerful approach to study the taxonomic composition and functional status of the microbiome under study. In this study, the mass spectrometry (MS)-based data of nasopharyngeal swab samples from COVID-19 patients was used to investigate the metaproteome. We have established a robust bioinformatics workflow within the Galaxy platform, which includes (a) generation of a tailored database of the common respiratory tract pathogens, (b) database search using multiple search algorithms, and (c) verification of the detected microbial peptides. The microbial peptides detected in this study, belong to several opportunistic pathogens such as Streptococcus pneumoniae, Klebsiella pneumoniae, Rhizopus microsporus, and Syncephalastrum racemosum. Microbial proteins with a role in stress response, gene expression, and DNA repair were found to be upregulated in severe patients compared to negative patients. Using parallel reaction monitoring (PRM), we confirmed some of the microbial peptides in fresh clinical samples. MS-based clinical metaproteomics can serve as a powerful tool for detection and characterization of potential pathogens, which can significantly impact the diagnosis and treatment of patients.

Genomic analysis of Enterococcus faecium strain RAOG174 associated with acute chorioamnionitis carried antibiotic resistance gene: is it time for precise microbiological identification for appropriate antibiotic use?

BACKGROUND

Preterm labor syndrome is associated with high perinatal morbidity and mortality, and intra-amniotic infection is a cause of preterm labor. The standard identification of causative microorganisms is based on the use of biochemical phenotypes, together with broth dilution-based antibiotic susceptibility from organisms grown in culture. However, such methods could not provide an accurate epidemiological aspect and a genetic basis of antimicrobial resistance leading to an inappropriate antibiotic administration. Hybrid genome assembly is a combination of short- and long-read sequencing, which provides better genomic resolution and completeness for genotypic identification and characterization. Herein, we performed a hybrid whole genome assembly sequencing of a pathogen associated with acute histologic chorioamnionitis in women presenting with PPROM.

RESULTS

We identified Enterococcus faecium, namely E. faecium strain RAOG174, with several antibiotic resistance genes, including vancomycin and aminoglycoside. Virulence-associated genes and potential bacteriophage were also identified in this genome.

CONCLUSION

We report herein the first study demonstrating the use of hybrid genome assembly and genomic analysis to identify E. faecium ST17 as a pathogen associated with acute histologic chorioamnionitis. The analysis provided several antibiotic resistance-associated genes/mutations and mobile genetic elements. The occurrence of E. faecium ST17 raised the awareness of the colonization of clinically relevant E. faecium and the carrying of antibiotic resistance. This finding has brought the advantages of genomic approach in the identification of the bacterial species and antibiotic resistance gene for E. faecium for appropriate antibiotic use to improve maternal and neonatal care.

Clinical metagenomics-challenges and future prospects

Infections lacking precise diagnosis are often caused by a rare or uncharacterized pathogen, a combination of pathogens, or a known pathogen carrying undocumented or newly acquired genes. Despite medical advances in infectious disease diagnostics, many patients still experience mortality or long-term consequences due to undiagnosed or misdiagnosed infections. Thus, there is a need for an exhaustive and universal diagnostic strategy to reduce the fraction of undocumented infections. Compared to conventional diagnostics, metagenomic next-generation sequencing (mNGS) is a promising, culture-independent sequencing technology that is sensitive to detecting rare, novel, and unexpected pathogens with no preconception. Despite the fact that several studies and case reports have identified the effectiveness of mNGS in improving clinical diagnosis, there are obvious shortcomings in terms of sensitivity, specificity, costs, standardization of bioinformatic pipelines, and interpretation of findings that limit the integration of mNGS into clinical practice. Therefore, physicians must understand the potential benefits and drawbacks of mNGS when applying it to clinical practice. In this review, we will examine the current accomplishments, efficacy, and restrictions of mNGS in relation to conventional diagnostic methods. Furthermore, we will suggest potential approaches to enhance mNGS to its maximum capacity as a clinical diagnostic tool for identifying severe infections.

Benchmarking of two bioinformatic workflows for the analysis of whole-genome sequenced Staphylococcus aureus collected from patients with suspected sepsis

BACKGROUND

The rapidly growing area of sequencing technologies, and more specifically bacterial whole-genome sequencing, could offer applications in clinical microbiology, including species identification of bacteria, prediction of genetic antibiotic susceptibility and virulence genes simultaneously. To accomplish the aforementioned points, the commercial cloud-based platform, 1928 platform (1928 Diagnostics, Gothenburg, Sweden) was benchmarked against an in-house developed bioinformatic pipeline as well as to reference methods in the clinical laboratory.

METHODS

Whole-genome sequencing data retrieved from 264 Staphylococcus aureus isolates using the Illumina HiSeq X next-generation sequencing technology was used. The S. aureus isolates were collected during a prospective observational study of community-onset severe sepsis and septic shock in adults at Skaraborg Hospital, in the western region of Sweden. The collected isolates were characterized according to accredited laboratory methods i.e., species identification by MALDI-TOF MS analysis and phenotypic antibiotic susceptibility testing (AST) by following the EUCAST guidelines. Concordance between laboratory methods and bioinformatic tools, as well as concordance between the bioinformatic tools was assessed by calculating the percent of agreement.

RESULTS

There was an overall high agreement between predicted genotypic AST and phenotypic AST results, 98.0% (989/1006, 95% CI 97.3-99.0). Nevertheless, the 1928 platform delivered predicted genotypic AST results with lower very major error rates but somewhat higher major error rates compared to the in-house pipeline. There were differences in processing times i.e., minutes versus hours, where the 1928 platform delivered the results faster. Furthermore, the bioinformatic workflows showed overall 99.4% (1267/1275, 95% CI 98.7-99.7) agreement in genetic prediction of the virulence gene characteristics and overall 97.9% (231/236, 95% CI 95.0-99.2%) agreement in predicting the sequence types (ST) of the S. aureus isolates.

CONCLUSIONS

Altogether, the benchmarking disclosed that both bioinformatic workflows are able to deliver results with high accuracy aiding diagnostics of severe infections caused by S. aureus. It also illustrates the need of international agreement on quality control and metrics to facilitate standardization of analytical approaches for whole-genome sequencing based predictions.

Coliform pollution mapping in major watersheds along Jhelum River Basin of Kashmir Himalaya

Coliform pollution for the last three decades in major river systems of the world has resulted in far ranging impacts on water quality. In this context, the present study aimed to assess the levels of indicator bacteria like total Coliform (TC), fecal Coliform (FC) and fecal Streptococcus (FS) in major watersheds of Kashmir valley. Sampling was carried out for a period of 2 years (summer 2017 to spring 2019) along several upstream, midstream and downstream reaches of Jhelum River Basin (JRB), while analysis was carried out by multiple tube fermentation technique involving Most Probable Number (MPN). Major highlights of the results revealed high levels of TC, FC and FS among downstream sites with pronounced seasonal variations between summer and winter. TC was highest at all the reaches and during all the seasons followed by FC and FS. Non-metric multidimensional scaling (NMDS) revealed more variation in Coliform count among reaches as compared to seasons. Mantle test revealed that environmental factors like observable environmental pressure (OEP) (r: 0.235, p < 0.0001), DO (r: 0.2815, p < 0.0001) and temperature (r: 0.04419, p = 0.0104) had prominent effect on Coliform distribution as compared to geographical factors. The study thus highlights the prevalence of Coliform bacteria along JRB resulting from fecal sources. Due to growing urbanization and lack of adequate sewage treatment facilities, there is an increase in the levels of Coliform bacteria along downstream reaches especially those residing within lower Jhelum and Dara watershed, which could jeopardize water quality and public health.

Statistical and Computational Methods for Microbial Strain Analysis

Microbial strains are interpreted as a lineage derived from a recent ancestor that have not experienced "too many" recombination events and can be successfully retrieved with culture-independent techniques using metagenomic sequencing. Such a strain variability has been increasingly shown to display additional phenotypic heterogeneities that affect host health, such as virulence, transmissibility, and antibiotics resistance. New statistical and computational methods have recently been developed to track the strains in samples based on shotgun metagenomics data either based on reference genome sequences or Metagenome-assembled genomes (MAGs). In this paper, we review some recent statistical methods for strain identifications based on frequency counts at a set of single nucleotide variants (SNVs) within a set of single-copy marker genes. These methods differ in terms of whether reference genome sequences are needed, how SNVs are called, what methods of deconvolution are used and whether the methods can be applied to multiple samples. We conclude our review with areas that require further research.

Development of ELISA-based diagnostic methods for the detection of haemorrhagic septicaemia in animals

Haemorrhagic septicaemia (HS) is an acute infection of cattle and buffaloes caused by the B:2 serotype of Pasteurella multocida. This disease is highly endemic in South Asia. In some peracute cases, there is 100% mortality in infected animals within a few hours of infection. Therefore, timely diagnosis of infection may contribute to its treatment and control to minimize economic losses. The current work reported the development of ELISA-based assays for the detection of anti-P. multocida antibodies and pathogen i.e. P. multocida. Owing to high immunogenicity, membrane proteins (MPs) extracted from local isolates of P. multocida serotype B:2 (PM1, PM2, and PM3) were employed as a potential diagnostic antigen for the development of indirect ELISA (i-ELISA) to detect HS antibodies in animals. MPs extracted from PM1, PM2 and PM3 isolates showed very low heterogeneity; hence MPs from the PM3 isolate were selected for the development of i-ELISA. The concentration of MPs (as coating antigen) of 3.13 μg/well and test sera dilution 1:100 was found to be optimal to perform i-ELISA. The developed method was validated through the detection of anti-P. multocida antibodies in sera of mice, immunized with MPs and formalin killed cells from the three local isolates (PM1, PM2 and PM3) of P. multocida. The significantly higher antibody titer in immunized mice was determined compared to unimmunized mice with the cut off value of 0.139. To detect P. multocida directly from the blood of infected animals, whole cell-based ELISA (cb-ELISA) assay was developed. A better detection signal was observed in the assay where bacterial cells were directly adsorbed on plate wells as compared to poly L-lysine (PLL) assisted attachment at a cell concentration of 10⁶ CFU and 10⁷ CFU respectively. The developed assays can be scaled up and potentially be used for the rapid detection of HS antibodies to gauge the immune status of the animal as well as vaccination efficacy and pathogen detection.

Next-Generation Sequencing Applications for the Study of Fungal Pathogens

Next-generation sequencing (NGS) has become a widely used technology in biological research. NGS applications for clinical pathogen detection have become vital technologies. It is increasingly common to perform fast, accurate, and specific detection of clinical specimens using NGS. Pathogenic fungi with high virulence and drug resistance cause life-threatening clinical infections. NGS has had a significant biotechnological impact on detecting bacteria and viruses but is not equally applicable to fungi. There is a particularly urgent clinical need to use NGS to help identify fungi causing infections and prevent negative impacts. This review summarizes current research on NGS applications for fungi and offers a visual method of fungal detection. With the development of NGS and solutions for overcoming sequencing limitations, we suggest clinicians test specimens as soon as possible when encountering infections of unknown cause, suspected infections in vital organs, or rapidly progressive disease.

What Can Genetics Do for the Control of Infectious Diseases in Aquaculture?

Simple Summary

Infectious diseases place an economic burden on aquaculture and a limitation to its growth. This state-of-the-art review describes the application of genetics and genomics as novel tools to control infectious disease in aquaculture.

Abstract

Infectious diseases place an economic burden on aquaculture and a limitation to its growth. An innovative approach to mitigate their impact on production is breeding for disease resistance: selection for domestication, family-based selection, marker-assisted selection, and more recently, genomic selection. Advances in genetics and genomics approaches to the control of infectious diseases are key to increasing aquaculture efficiency, profitability, and sustainability and to reducing its environmental footprint. Interaction and co-evolution between a host and pathogen can, however, turn breeding to boost infectious disease resistance into a potential driver of pathogenic change. Parallel molecular characterization of the pathogen and its virulence and antimicrobial resistance genes is therefore essential to understand pathogen evolution over time in response to host immunity, and to apply appropriate mitigation strategies.

Ecological Observations Based on Functional Gene Sequencing Are Sensitive to the Amplicon Processing Method

Until recently, the de facto method for short-read-based amplicon reconstruction was a sequence similarity threshold approach (operational taxonomic units [OTUs]). This has changed with the amplicon sequence variant (ASV) method where distributions are fitted to abundance profiles of individual genes using a noise-error model. While OTU-based approaches are still useful for 16S rRNA/18S rRNA genes, where thresholds of 97% to 99% are used, their use for functional genes is still debatable as there is no consensus on clustering thresholds. Here, we compare OTU- and ASV-based reconstruction approaches and taxonomy assignment methods, the naive Bayesian classifier (NBC) and Bayesian lowest common ancestor (BLCA) algorithm, using a functional gene data set from the microbial nitrogen-cycling community in the Brouage mudflat (France). A range of OTU similarity thresholds and ASVs were used to compare amoA (ammonia-oxidizing archaea [AOA] and ammonia-oxidizing bacteria [AOB]), nxrB, nirS, nirK, and nrfA communities between differing sedimentary structures. Significant effects of the sedimentary structure on weighted UniFrac (WUniFrac) distances were observed for AOA amoA when using ASVs, an OTU at a threshold of 97% sequence identity (OTU-97%), and OTU-85%; AOB amoA when using OTU-85%; and nirS when using ASV, OTU-90%, and OTU-85%. For AOB amoA, significant effects of the sedimentary structures on UniFrac distances were observed when using OTU-97% but not ASVs, and the inverse was found for nrfA. Interestingly, conclusions drawn for nirK and nxrB were consistent between amplicon reconstruction methods. We also show that when the sequences in the reference database are related to the environment in question, the BLCA algorithm leads to more phylogenetically relevant classifications. However, when the reference database contains sequences more dissimilar to the ones retrieved, the NBC obtains more information. IMPORTANCE Several analysis pipelines are available to microbial ecologists to process amplicon sequencing data, yet to date, there is no consensus as to the most appropriate method, and it becomes more difficult for genes that encode a specific function (functional genes). Standardized approaches need to be adopted to increase the reliability and reproducibility of environmental amplicon-sequencing-based data sets. In this paper, we argue that the recently developed ASV approach offers a better opportunity to achieve such standardization than OTUs for functional genes. We also propose a comprehensive framework for quality filtering of the sequencing reads based on protein sequence verification.

Laboratory diagnosis of urinary tract infections in patients with resistance genes towards antibiotics

Escherichia coli are gram-negative bacteria that cause urinary tract infections (UTIs). UTIs have affected a significant percentage of humans yearly due to bacterial infection. Our study aims to determine the prevalence of resistance genes in E. coli towards sulfamethoxazole. This study included (490) patients with UTIs, and the urine samples were cultured on media. The patients were admitted to the Medical City in Baghdad to treat UTIs. 116 E.coli isolates were isolated from urine specimens, 35 isolates of them were resistant to trimethoprim/sulfamethoxazole, and 81 isolates were sensitive to trimethoprim/sulfamethoxazole; the E. coli isolates were submitted to multiplex PCR to detection some resistance genes (Sul1, sul2) after detected the isolates by PCR depending on 16S rRNA. Our study showed that identified E. coli was (91-99%) depending on the number of the examined samples by the Vitek 2 system. The molecular study included extraction of chromosomal DNA from (53) E. coli isolates; 35 samples were taken resistant to antibiotics, while from the total of 81 sensitive isolates, only 18 sensitive samples were taken from that are the most sensitive to Timethprime/sulfamethoxazole, then identification by 16S rRNA gene. Detection of Sulfonamides resistance genes included sul1 and sul2. The results showed the 16S rRNA gene identification found in all E. coli isolates and the detection of antibiotic resistance genes. The resistant isolates with the Sul1 gene prevalence were 11(31%), while the sensitive isolates with Sul1gene were 1(6%). Moreover, the resisted isolates with Sul2 gene prevalence was 8(23%), while the sensitive isolates with the Sul1 gene were 0(0%). The numbers of the resistant isolates were (11) and (8) that carry the Sul1 gene and Sul2 gene, respectively, while the numbers of the sensitive isolates were (1) and (0), respectively. We can conclude that a high percentage of Sul1 gene and Sul2 genes in E. coil isolated from UTIs were high. Keywords. UTI, Sul1, Sul2, resistant gene, trimethoprim-sulfamethoxazole

Neurosyphilis with a rare magnetic resonance imaging pattern confirmed by metagenomic next-generation sequencing: a case report

Background

Neurosyphilis refers to infection of the central nervous system by Treponema pallidum. The clinical presentation is variable and nonspecific. Neuroimaging findings are complex and that the diagnosis is based on clinical presentation, cerebrospinal fluid (CSF) parameters, and serologic and CSF evidence of syphilis. To date, there is no case report describing Treponema pallidum detected by metagenomic next-generation sequencing (mNGS) in CSF.

Case presentation

In this report, we describe a case of neurosyphilis in a HIV-negative, 29-year-old man, who was admitted to our hospital with an epileptic seizure and progressive cognitive impairment. Brain magnetic resonance imaging (MRI) revealed fluid-attenuated inversion recovery (FLAIR) high signal intensities in bilateral medial and anterior temporal lobes, insula, right pulvinar of the thalami, precuneus, frontal and temporo-occipital lobes. Laboratory examination showed positive results by means of nontreponemal or specific treponemal test in serum and CSF. mNGS of the CSF was also performed to identify Treponema pallidum for the first time.

Conclusions

This case underscores the importance of considering neurosyphilis as a potential cause of mesiotemporal abnormality. In addition, the rapid improvement and wide usability of mNGS technology will bring new breakthroughs in the clinical diagnosis of neurosyphilis.

Prevalence and Molecular Characterization of Mycoplasma Species, Pasteurella multocida, and Staphylococcus aureus Isolated from Calves with Respiratory Manifestations

Bovine respiratory disease (BRD) is a complex syndrome associated with high mortality in young calves and causes severe economic losses in the cattle industry worldwide. The current study investigated the prevalence and molecular characterization of common bacterial pathogens associated with respiratory symptoms in young calves from Sadat City, one of the largest industrial cities in Menoufiya Governorate, Egypt. In between December 2020 and March 2021, 200 mixed-breed young calves of 6–12 months were examined clinically. Of them, sixty (30%) calves showed signs of respiratory manifestations, such as coughing, serous to mucopurulent nasal discharges, fever, and abnormal lung sound. Deep nasal (Nasopharyngeal) swabs were collected from the affected calves for bacteriological investigation. Phenotypic characterization and identification revealed Mycoplasma bovis, Mycoplasma bovigenitalium, Pasteurella multocida, and Staphylococcus aureus in 8.33%, 5%, 5%, and 5% of the tested samples, respectively. The PCR technique using species-specific primer sets successfully amplified the target bacterial DNA in all culture-positive samples, confirming the identity of the isolated bacterial species. Partial gene sequencing of 16S rRNA gene of M. bovigenitalium, P. multocida, and S. aureus, and mb-mp 81 gene of M. bovis revealed high nucleotide similarity and genetic relationship with respective bacterial species reported from Egypt and around the world, suggesting transmission of these bacterial species between animal host species and localities. Our study highlights the four important bacterial strains associated with respiratory disorders in calves and suggests the possible spread of these bacterial pathogens across animal species and different geographic locations. Further studies using WGS and a large number of isolates are required to investigate the realistic lineage of Egyptian isolates and globally.

High-throughput sequencing technologies in the detection of livestock pathogens, diagnosis, and zoonotic surveillance

Increasing globalization, agricultural intensification, urbanization, and climatic changes have resulted in a significant recent increase in emerging infectious zoonotic diseases. Zoonotic diseases are becoming more common, so innovative, effective, and integrative research is required to better understand their transmission, ecological implications, and dynamics at wildlife-human interfaces. High-throughput sequencing (HTS) methodologies have enormous potential for unraveling these contingencies and improving our understanding, but they are only now beginning to be realized in livestock research. This study investigates the current state of use of sequencing technologies in the detection of livestock pathogens such as bovine, dogs (Canis lupus familiaris), sheep (Ovis aries), pigs (Sus scrofa), horses (Equus caballus), chicken (Gallus gallus domesticus), and ducks (Anatidae) as well as how it can improve the monitoring and detection of zoonotic infections. We also described several high-throughput sequencing approaches for improved detection of known, unknown, and emerging infectious agents, resulting in better infectious disease diagnosis, as well as surveillance of zoonotic infectious diseases. In the coming years, the continued advancement of sequencing technologies will improve livestock research and hasten the development of various new genomic and technological studies on farm animals.

Clinical Evaluation of a Metagenomics-Based Assay for Pneumonia Management

Clinical value of metagenomic next-generation sequencing (mNGS) in pneumonia management is still controversial. A prospective study was conducted to evaluate the clinical impact of PneumoSeq in 57 immunocompetent (ICO) and 75 immunocompromised (ICH) pneumonia patients. The value of PneumoSeq for both etiological and clinical impact investigation in pneumonia was assessed. Among the 276 potential pathogens detected with PneumoSeq in our cohort, 251 (90.9%) were cross-validated. Clinical diagnoses of the causative pathogens were obtained for 97 patients, 90.7% of which were supported by PneumoSeq. Compared to conventional testing, PneumoSeq suggested potentially missed diagnoses in 16.7% of cases (22/132), involving 48 additional pathogenic microorganisms. In 58 (43.9%) cases, PneumoSeq data led to antimicrobial treatment de-escalation (n = 12 in ICO, n = 18 in ICH) and targeted treatment initiation (n = 7 in ICO, n = 21 in ICH). The PneumoSeq assay benefited the diagnosis and clinical management of both ICH and ICO pneumonia patients in real-world settings.

Applications of Raman Spectroscopy in Bacterial Infections: Principles, Advantages, and Shortcomings

Infectious diseases caused by bacterial pathogens are important public issues. In addition, due to the overuse of antibiotics, many multidrug-resistant bacterial pathogens have been widely encountered in clinical settings. Thus, the fast identification of bacteria pathogens and profiling of antibiotic resistance could greatly facilitate the precise treatment strategy of infectious diseases. So far, many conventional and molecular methods, both manual or automatized, have been developed for in vitro diagnostics, which have been proven to be accurate, reliable, and time efficient. Although Raman spectroscopy (RS) is an established technique in various fields such as geochemistry and material science, it is still considered as an emerging tool in research and diagnosis of infectious diseases. Based on current studies, it is too early to claim that RS may provide practical guidelines for microbiologists and clinicians because there is still a gap between basic research and clinical implementation. However, due to the promising prospects of label-free detection and noninvasive identification of bacterial infections and antibiotic resistance in several single steps, it is necessary to have an overview of the technique in terms of its strong points and shortcomings. Thus, in this review, we went through recent studies of RS in the field of infectious diseases, highlighting the application potentials of the technique and also current challenges that prevent its real-world applications.

Challenge of diagnosing acute infections in poor resource settings in Africa

Frequent disease outbreaks and acute infections occur in rural and low-income urban areas of Africa, with many health systems unprepared to diagnose and control diseases that are recurrent, endemic or have extended their geographic zone. In this review, we focus on acute infections that can be characterized by sudden onset, rapid progression, severe symptoms and poor prognosis. Consequently, these infections require early diagnosis and intervention. While effective vaccines have been developed against some of these diseases, lack of compliance and accessibility, and the need for repeated or multiple vaccinations mean large populations can remain vulnerable to infection. It follows that there is a need for enhancement of national surveillance and diagnostic capacity to avert morbidity and mortality from acute infections. We discuss the limitations of traditional diagnostic methods and explore the relative merits and applicability of protein-, carbohydrate- and nucleic acid-based rapid diagnostic tests that have been trialled for some infectious diseases. We also discuss the utility and limitations of antibody-based serological diagnostics and explore how systems biology approaches can better inform diagnosis. Lastly, given the complexity and high cost associated with after-service support of emerging technologies, we propose that, for resource-limited settings in Africa, multiplex point-of-care diagnostic tools be tailor-made to detect both recurrent acute infections and endemic infections.

Genomic analysis on Brazilian strains of Anaplasma marginale

Anaplasma marginale is a vector-borne pathogen that causes a disease known as anaplasmosis. No sequenced genomes of Brazilian strains are yet available. The aim of this work was to compare whole genomes of Brazilian strains of A. marginale (Palmeira and Jaboticabal) with genomes of strains from other regions (USA and Australia strains). Genome sequencing of Brazilian strains was performed by means of next-generation sequencing. Reads were mapped using the genome of the Florida strain of A. marginale as a reference sequence. Single nucleotide polymorphisms (SNPs) and insertions/deletions (INDELs) were identified. The data showed that two Brazilian strains grouped together in one particular clade, which grouped in a larger American group together with North American strains. Moreover, some important differences in surface proteins between the two Brazilian isolates can be discerned. These results shed light on the evolutionary history of A. marginale and provide the first genome information on South American isolates. Assessing the genome sequences of strains from different regions is essential for increasing knowledge of the pan-genome of this bacteria.

Ultra-fast and universal detection of Gram-negative bacteria in complex samples based on colistin derivatives

Gram-negative bacteria are a significant cause of infections acquired in both hospital and community settings, resulting in a high mortality rate worldwide. Currently, a Gram-negative infection is diagnosed by symptom evaluation and is treated with empiric antibiotics which target both Gram-negative and Gram-positive bacteria. A rapid and simple diagnostic method would enable immediate and targeted treatment, while dramatically reducing antibiotic overuse. Herein, we introduce a method utilizing a fluorescent derivative of colistin (COL-FL), that can directly label the Gram-negative cell wall of live bacteria and universally detect the targets within 10 min. By using the COL-FL assay, we achieved the differential labeling of various Gram-negative pathogens related to hospital-acquired infections, which could be subsequently detected via spectrofluorometry and microscopy. Further, we determined that our method can be used for complex samples, such as combinations of multiple bacterial types; bacteria in the presence of mammalian cells; and bacteria with serum components. This assay can be integrated into a simple diagnostic platform for rapid screening tests and the stratification of Gram-negative bacterial infections in the clinic.

Advantages and Limitations of 16S rRNA Next-Generation Sequencing for Pathogen Identification in the Diagnostic Microbiology Laboratory: Perspectives from a Middle-Income Country

Bacterial culture and biochemical testing (CBtest) have been the cornerstone of pathogen identification in the diagnostic microbiology laboratory. With the advent of Sanger sequencing and later, next-generation sequencing, 16S rRNA next-generation sequencing (16SNGS) has been proposed to be a plausible platform for this purpose. Nevertheless, usage of the 16SNGS platform has both advantages and limitations. In addition, transition from the traditional methods of CBtest to 16SNGS requires procurement of costly equipment, timely and sustainable maintenance of these platforms, specific facility infrastructure and technical expertise. All these factors pose a challenge for middle-income countries, more so for countries in the lower middle-income range. In this review, we describe the basis for CBtest and 16SNGS, and discuss the limitations, challenges, advantages and future potential of using 16SNGS for bacterial pathogen identification in diagnostic microbiology laboratories of middle-income countries.

Diagnostic approaches and contribution of next-generation sequencing technologies in genomic investigation of Vibrio parahaemolyticus that caused acute hepatopancreatic necrosis disease (AHPND)

A unique strain of Vibrio parahaemolyticus (designated as VP_AHPND) causes acute hepatopancreatic necrosis disease (AHPND), a deadly bacterial disease associated with mass mortality in cultured shrimps since 2009. AHPND is responsible for severe economic losses worldwide, causing multimillion-dollar loss annually. Because of the rapid and high mortality rates in shrimps, substantial research has been carried out to develop rapid detection techniques. Also, recent technological advances such as the next-generation sequencing (NGS) have made it possible to elucidate relevant information about a pathogen in a single assay. This review summarizes the current research pertaining to VP_AHPND, focusing on diagnosis and contribution of NGS technologies in the genomic studies of AHPND.

Stochastic determination of the spatial variation of potentially pathogenic bacteria communities in a large subtropical river

Understanding the composition and assembly mechanism of waterborne pathogen is essential for preventing the pathogenic infection and protecting the human health. Here, based on 16S rRNA sequencing, we investigated the composition and spatial variation of potentially pathogenic bacteria from different sections of the Pearl River, the most important source of water for human in Southern China. The results showed that the potential pathogen communities consisted of 6 phyla and 64 genera, covering 11 categories of potential pathogens mainly involving animal parasites or symbionts (AniP), human pathogens all (HumPA), and intracellular parasites (IntCelP). Proteobacteria (75.87%) and Chlamydiae (20.56%) were dominant at the phylum level, and Acinetobacter (35.01%) and Roseomonas (8.24%) were dominant at the genus level. Multivariate analysis showed that the potential pathogenic bacterial community was significantly different among the four sections in the Pearl River. Both physicochemical factors (e.g., NO₃-N, and suspended solids) and land use (e.g., urban land and forest) significantly shaped the pathogen community structure. However, spatial effects contributed more to the variation of pathogen community based on variation partitioning and path analysis. Null model based normalized stochasticity ratio analysis further indicated that the stochastic process rather than deterministic process dominated the assembly mechanisms by controlling the spatial patterns of potential pathogens. In conclusion, high-throughput sequencing shows great potential for monitoring the potential pathogens, and provided more comprehensive information on the potentially pathogenic community. Our study highlighted the importance of considering the influences of dispersal-related processes in future risk assessments for the prevention and control of pathogenic bacteria.

Computational Methods for Strain-Level Microbial Detection in Colony and Metagenome Sequencing Data

Metagenomic sequencing is a powerful tool for examining the diversity and complexity of microbial communities. Most widely used tools for taxonomic profiling of metagenomic sequence data allow for a species-level overview of the composition. However, individual strains within a species can differ greatly in key genotypic and phenotypic characteristics, such as drug resistance, virulence and growth rate. Therefore, the ability to resolve microbial communities down to the level of individual strains within a species is critical to interpreting metagenomic data for clinical and environmental applications, where identifying a particular strain, or tracking a particular strain across a set of samples, can help aid in clinical diagnosis and treatment, or in characterizing yet unstudied strains across novel environmental locations. Recently published approaches have begun to tackle the problem of resolving strains within a particular species in metagenomic samples. In this review, we present an overview of these new algorithms and their uses, including methods based on assembly reconstruction and methods operating with or without a reference database. While existing metagenomic analysis methods show reasonable performance at the species and higher taxonomic levels, identifying closely related strains within a species presents a bigger challenge, due to the diversity of databases, genetic relatedness, and goals when conducting these analyses. Selection of which metagenomic tool to employ for a specific application should be performed on a case-by case basis as these tools have strengths and weaknesses that affect their performance on specific tasks. A comprehensive benchmark across different use case scenarios is vital to validate performance of these tools on microbial samples. Because strain-level metagenomic analysis is still in its infancy, development of more fine-grained, high-resolution algorithms will continue to be in demand for the future.

Human microbiome: an academic update on human body site specific surveillance and its possible role

Human body is inhabited by vast number of microorganisms which form a complex ecological community and influence the human physiology, in the aspect of both health and diseases. These microbes show a relationship with the human immune system based on coevolution and, therefore, have a tremendous potential to contribute to the metabolic function, protection against the pathogen and in providing nutrients and energy. However, of these microbes, many carry out some functions that play a crucial role in the host physiology and may even cause diseases. The introduction of new molecular technologies such as transcriptomics, metagenomics and metabolomics has contributed to the upliftment on the findings of the microbiome linked to the humans in the recent past. These rapidly developing technologies are boosting our capacity to understand about the human body-associated microbiome and its association with the human health. The highlights of this review are inclusion of how to derive microbiome data and the interaction between human and associated microbiome to provide an insight on the role played by the microbiome in biological processes of the human body as well as the development of major human diseases.

New solutions to capture and enrich bacteria from complex samples

Current solutions to diagnose bacterial infections though reliable are often time-consuming, laborious and need a specific laboratory setting. There is an unmet need for bedside accurate diagnosis of infectious diseases with a short turnaround time. Moreover, low-cost diagnostics will greatly benefit regions with poor resources. Immunoassays and molecular techniques have been used to develop highly sensitive diagnosis solutions but retaining many of the abovementioned limitations. The detection of bacteria in a biological sample can be enhanced by a previous step of capture and enrichment. This will ease the following process enabling a more sensitive detection and increasing the possibility of a conclusive identification in the downstream diagnosis. This review explores the latest developments regarding the initial steps of capture and enrichment of bacteria from complex samples with the ultimate goal of designing low cost and reliable diagnostics for bacterial infections. Some solutions use specific ligands tethered to magnetic constructs for separation under magnetic fields, microfluidic platforms and engineered nano-patterned surfaces to trap bacteria. Bulk acoustics, advection and nano-filters comprise some of the most innovative solutions for bacteria enrichment.

Re-addressing the biosafety issues of plant growth promoting rhizobacteria

To promote agronomic sustainability, extensive research is being carried out globally, investigating biofertilizer development. Recently, it has been realized that some microorganisms used as biofertilizers behave as opportunistic pathogens and belong to the biosafety level 2 (BSL-2) classification. This poses serious risk to the environmental and human health. Evidence presented in various scientific forums is increasingly favoring the merits of using BSL-2 microorganisms as biofertilizers. In this review, we emphasize that partial characterization based on traditional microbiological approaches and small subunit rRNA gene sequences/conserved regions are insufficient for the characterization of biofertilizer strains. It is advised herein, that research and industrial laboratories developing biofertilizers for commercialization or environmental release must characterize microorganisms of interest using a multilateral polyphasic approach of microbial systematics. This will determine their risk group and biosafety characteristics before proceeding with formulation development and environmental application. It has also been suggested that microorganisms belonging to risk-group-1 and BSL-1 category should be used for formulation development and for field scale applications. While, BSL-2 microorganisms should be restricted for research using containment practices compliant with strict regulations.

Bacterial infections in acute exacerbation of chronic obstructive pulmonary disease: a systematic review and meta-analysis

OBJECTIVE

Due to the importance of Chronic obstructive pulmonary disease (COPD) as the fourth cause of mortality worldwide and the lack of studies evaluating the prevalence of bacterial infections in disease exacerbation, this systematic review and meta-analysis was performed to determine the prevalence rate of bacterial infections in COPD patients.

METHODS

PubMed, ISI Web of Science, and Scopus databases were systematically searched for population-based prevalence studies (1980-2018). MeSH terms for "Bacterial infections" and "AECOPD" were used as search keywords. The selected studies were filtered according to the inclusion and exclusion criteria. Fixed and random-effects models were used for estimation of summary effect sizes. Between-study heterogeneity, as well as publication bias, were calculated.

RESULTS

Finally, 118 out of 31,440 studies were selected. The overall estimation of the prevalence of bacterial infection was 49.59% [95% confidence interval (CI) 0.4418-0.55]. The heterogeneity in estimating the pooled prevalence of bacterial infections was shown in the studies (Cochran Q test: 6615, P < 0.0001, I² = 98.23%). In addition, S. pneumoniae, H. influenzae, M. catarrhalis, A. baumannii, P. aeruginosa, and S. aureus were the most prevalent reported bacteria.

CONCLUSIONS

Our results as the first meta-analysis for the issue demonstrated that bacterial infections are an important risk factor for AECOPD. Further studies must be performed for understanding the exact role of bacterial agents in AECOPD and help physicians for more applicable preventive and therapeutic measurements.

Status and potential of bacterial genomics for public health practice: a scoping review

Background

Next-generation sequencing (NGS) is increasingly being translated into routine public health practice, affecting the surveillance and control of many pathogens. The purpose of this scoping review is to identify and characterize the recent literature concerning the application of bacterial pathogen genomics for public health practice and to assess the added value, challenges, and needs related to its implementation from an epidemiologist’s perspective.

Methods

In this scoping review, a systematic PubMed search with forward and backward snowballing was performed to identify manuscripts in English published between January 2015 and September 2018. Included studies had to describe the application of NGS on bacterial isolates within a public health setting. The studied pathogen, year of publication, country, number of isolates, sampling fraction, setting, public health application, study aim, level of implementation, time orientation of the NGS analyses, and key findings were extracted from each study. Due to a large heterogeneity of settings, applications, pathogens, and study measurements, a descriptive narrative synthesis of the eligible studies was performed.

Results

Out of the 275 included articles, 164 were outbreak investigations, 70 focused on strategy-oriented surveillance, and 41 on control-oriented surveillance. Main applications included the use of whole-genome sequencing (WGS) data for (1) source tracing, (2) early outbreak detection, (3) unraveling transmission dynamics, (4) monitoring drug resistance, (5) detecting cross-border transmission events, (6) identifying the emergence of strains with enhanced virulence or zoonotic potential, and (7) assessing the impact of prevention and control programs. The superior resolution over conventional typing methods to infer transmission routes was reported as an added value, as well as the ability to simultaneously characterize the resistome and virulome of the studied pathogen. However, the full potential of pathogen genomics can only be reached through its integration with high-quality contextual data.

Conclusions

For several pathogens, it is time for a shift from proof-of-concept studies to routine use of WGS during outbreak investigations and surveillance activities. However, some implementation challenges from the epidemiologist’s perspective remain, such as data integration, quality of contextual data, sampling strategies, and meaningful interpretations. Interdisciplinary, inter-sectoral, and international collaborations are key for an appropriate genomics-informed surveillance.

Electronic supplementary material

The online version of this article (10.1186/s13012-019-0930-2) contains supplementary material, which is available to authorized users.

Exploring the Hospital Microbiome by High-Resolution 16S rRNA Profiling

The aim of this work was to analyze and compare the bacterial communities of 663 samples from a Brazilian hospital by using high-throughput sequencing of the 16S rRNA gene. To increase taxonomic profiling and specificity of 16S-based identification, a strict sequence quality filtering process was applied for the accurate identification of clinically relevant bacterial taxa. Our results indicate that the hospital environment is predominantly inhabited by closely related species. A massive dominance of a few taxa in all taxonomic levels down to the genera was observed, where the ten most abundant genera in each facility represented 64.4% of all observed taxa, with a major predominance of Acinetobacter and Pseudomonas. The presence of several nosocomial pathogens was revealed. Co-occurrence analysis indicated that the present hospital microbial network had low connectedness, forming a clustered topology, but not structured among groups of nodes (i.e., modules). Furthermore, we were able to detect ecologically relevant relationships between specific microbial taxa, in particular, potential competition between pathogens and non-pathogens. Overall, these results provide new insight into different aspects of a hospital microbiome and indicate that 16S rRNA sequencing may serve as a robust one-step tool for microbiological identification and characterization of a wide range of clinically relevant bacterial taxa in hospital settings with a high resolution.

Sequence similarity searches for morphine biosynthesis enzymes in bacteria yield putative targets for understanding associations between infection and opiate administration

Exploiting the immunosuppressive, analgesic and highly addictive properties of morphine could increase the success of a bacterial pathogen. Therefore, we performed sequence similarity searches for two morphine biosynthesis demethylases in bacteria. For thebaine 6-O-demethylase and codeine O-demethylase, we found strong alignments to three (Pseudomonas aeruginosa, Klebsiella pneumoniae and Acinetobacter baumannii) of the six ESKAPE pathogens (Enterococcus faecalis, Staphylococcus aureus, K. pneumoniae, A. baumannii, P. aeruginosa and Enterobacter species) that are commonly associated with drug resistance and nosocomial infections. Expression of the aligned sequence found in P. aeruginosa (NP_252880.1/PA4191) is upregulated in isolates obtained from cystic fibrosis patients. Our findings provide putative mechanistic targets for understanding the role of morphine in pathogenicity.

A high-throughput system used to determine frequency and distribution of phosphine resistance across large geographical regions

BACKGROUND

Next-generation sequencing can enable genetic surveys of large numbers of individuals. We developed a genotyping-by-sequencing assay for detecting strong phosphine resistance alleles in the dihydrolipoamide dehydrogenase (dld) gene of Rhyzopertha dominica populations. The assay can estimate the distribution and frequency of resistance variants in thousands of individual insects in a single run.

RESULTS

We analysed 1435 individual insects collected over a 1-year period from 59 grain-storage sites including farms (n = 29) and central storages (n = 30) across eastern Australia. Resistance alleles were detected in 49% of samples, 38% of farms and 60% of central storages. Although multiple alleles were detected, only two resistance variants (P49S and K142E) were widespread and each appeared to have a distinct but overlapping geographical distribution.

CONCLUSION

The type of structure in which the grain is stored had a strong effect on resistance allele frequency. We observed higher frequencies of resistance alleles in bunker storages at central sites compared with other storage types. This contributed to the higher frequencies of resistance alleles in bulk-handling facilities relative to farms. The discovery of a storage structure that predisposes insects to resistance highlights the utility of our high-throughput assay system for improvement of phosphine resistance management practices. © 2018 Society of Chemical Industry.

Genome-based taxonomic classification

Bacterial populations are routinely characterized based on microscopic examination, colony formation, and biochemical tests. However, in the recent past, bacterial identification, classification, and nomenclature have been strongly influenced by genome sequence information. Advances in bioinformatics and growth in genome databases has placed genome-based metadata analysis in the hands of researchers who will require taxonomic experience to resolve intricacies. To achieve this, different tools are now available to quantitatively measure genome relatedness within members of the same species, and genome-wide average nucleotide identity (gANI) is one such reliable tool to measure genome similarity. A genome assembly with a gANI score of <95% at the intraspecies level is generally considered indicative of a separate species. In this study, we have analysed 300 whole-genome sequences belonging to 26 different bacterial species available in the NCBI Genome database and calculated their similarity at the intraspecies level based on gANI score. At the intraspecies level, nine bacterial species showed less than 90% gANI and more than 10% of unaligned regions. We suggest the appropriate use of available bioinformatics resources after genome assembly to arrive at the proper bacterial identification, classification, and nomenclature to avoid erroneous species assignments and disparity due to diversity at the intraspecies level.

Epidemiological characterization of serotype group B Streptococci neonatal infections associated with interleukin-6 level as a sensitive parameter for the early diagnosis

Group B streptococcal infection (Streptococcus agalactiae) is one of the leading causes of life-threatening disease in the early neonatal period, resulting in sepsis, pneumonia, and meningitis. During invasive infections, an excessive release of pro-inflammatory cytokine, such as interleukin-6 (IL-6), thus IL-6 gene is significant, as a diagnostic marker of systemic infection of the newborns. The present study aimed to describe the epidemiology diagnostic of GBS disease in neonatal by phenotypic and genotypic methods. Nine hundred and ninety-six samples were taken at Maternity and Children Hospital, Jeddah, Saudi Arabia for a period of one year (2011-2012). Results indicated that out of 217 infected samples, twenty (9.23.0%) were positive for group B Streptococci bacteria. This study also shows that female infants are more susceptible than males. The level of IL-6 was higher in mothers above 30 years. Twenty positive Streptococci group B isolates showed bands with the cylE gene primers in the border between 228 bp, 267 bp and 50 bp. Molecular detection by Real time polymerase chain reaction was also done to detect the target (Sip gene) encoding the Sip surface immunogenic protein. Specific primers and TaqMan probe were chosen for this purpose. A Real-time PCR method targeting the sip gene of GBS in neonates after delivery has been evaluated.

Detecting Biothreat Agents: From Current Diagnostics to Developing Sensor Technologies

Although a fundamental understanding of the pathogenicity of most biothreat agents has been elucidated and available treatments have increased substantially over the past decades, they still represent a significant public health threat in this age of (bio)terrorism, indiscriminate warfare, pollution, climate change, unchecked population growth, and globalization. The key step to almost all prevention, protection, prophylaxis, post-exposure treatment, and mitigation of any bioagent is early detection. Here, we review available methods for detecting bioagents including pathogenic bacteria and viruses along with their toxins. An introduction placing this subject in the historical context of previous naturally occurring outbreaks and efforts to weaponize selected agents is first provided along with definitions and relevant considerations. An overview of the detection technologies that find use in this endeavor along with how they provide data or transduce signal within a sensing configuration follows. Current "gold" standards for biothreat detection/diagnostics along with a listing of relevant FDA approved in vitro diagnostic devices is then discussed to provide an overview of the current state of the art. Given the 2014 outbreak of Ebola virus in Western Africa and the recent 2016 spread of Zika virus in the Americas, discussion of what constitutes a public health emergency and how new in vitro diagnostic devices are authorized for emergency use in the U.S. are also included. The majority of the Review is then subdivided around the sensing of bacterial, viral, and toxin biothreats with each including an overview of the major agents in that class, a detailed cross-section of different sensing methods in development based on assay format or analytical technique, and some discussion of related microfluidic lab-on-a-chip/point-of-care devices. Finally, an outlook is given on how this field will develop from the perspective of the biosensing technology itself and the new emerging threats they may face.

The proper structure of a biosafety system as a way of reducing the vulnerability of a society, economy or state in the face of a biogenic threat

To understand how vulnerable are a society, an economy and a state in the face of a biohazard, one should attempt to identify any potential holes in the national biosafety system, such as the lack of important components or technologies for biological monitoring and the inadequacy of existing analytical methods used to prevent or counteract biogenic threats. In Russia, biological monitoring is quite advanced. However, the agencies that ensure proper functioning of its components lack collaboration and do not form a well-coordinated network. Each of such agencies alone cannot provide comprehensive information on the subject. In the Russian Federation, there are at least 4 state-funded programs that collect epidemiological data and are quite efficient in performing the narrow task of monitoring infections. But because there is no central database where epidemiological data can be channeled and subsequently shared, these agencies do not complete each other. This leaves the Russian society, economy and state vulnerable to biogenic threats. We need an adequately organized, modern, fully functional and effective system for monitoring biohazards that will serve as a basis for the national biosafety system and also a tool for the identification and elimination of its weaknesses.

Clostridioides difficile in the environment, food, animals and humans in southern Italy: Occurrence and genetic relatedness

One hundred and thirty-eight C. difficile isolates from different sources (66 from the environment, 36 from animals, 9 from food and 27 from humans) were ribotyped by capillary electrophoresis PCR ribotyping (CE-PCR). A multilocus variable tandem repeat analysis (MLVA) was carried out on a sample subset. The most frequently isolated PCR ribotypes were 126 (15.9%), 078 (14.5%), 011/018 (11.6%), 014/020/077 (10.1%), and 010 (2.8%). In particular, strains of PCR ribotype 011/018 were isolated from human, raw milk and environmental samples. The hypervirulent PCR ribotype 027 was isolated from two human samples. The majority of the strains were toxigenic (34.1% showed the toxigenic profile A⁺B⁺CDT⁺ and 38.9% the profile A⁺B⁺CDT^-). MLVA allowed to identify 4 clonal complexes of genetically related isolates: complex n. 1 grouped together human, environmental and food strains, whereas complex n. 3 included human and environmental isolates. The use of MLVA gave further evidence to the possible role of environment, animals and food as routes of transmission of C. difficile infections to human.

TOPAZ: asymmetric suffix array neighbourhood search for massive protein databases

Background

Protein homology search is an important, yet time-consuming, step in everything from protein annotation to metagenomics. Its application, however, has become increasingly challenging, due to the exponential growth of protein databases. In order to perform homology search at the required scale, many methods have been proposed as alternatives to BLAST that make an explicit trade-off between sensitivity and speed. One such method, SANSparallel, uses a parallel implementation of the suffix array neighbourhood search (SANS) technique to achieve high speed and provides several modes to allow for greater sensitivity at the expense of performance.

Results

We present a new approach called asymmetric SANS together with scored seeds and an alternative suffix array ordering scheme called optimal substitution ordering. These techniques dramatically improve both the sensitivity and speed of the SANS approach. Our implementation, TOPAZ, is one of the top performing methods in terms of speed, sensitivity and scalability. In our benchmark, searching UniProtKB for homologous proteins to the Dickeya solani proteome, TOPAZ took less than 3 minutes to achieve a sensitivity of 0.84 compared to BLAST.

Conclusions

Despite the trade-off homology search methods have to make between sensitivity and speed, TOPAZ stands out as one of the most sensitive and highest performance methods currently available.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2290-3) contains supplementary material, which is available to authorized users.

Identification and characterization of novel mosquito-borne (Kammavanpettai virus) and tick-borne (Wad Medani) reoviruses isolated in India

In 1954, a virus named Wad Medani virus (WMV) was isolated from Hyalomma marginatum ticks from Maharashtra State, India. In 1963, another virus was isolated from Sturnia pagodarum birds in Tamil Nadu, India, and named Kammavanpettai virus (KVPTV) based on the site of its isolation. Originally these virus isolates could not be identified with conventional methods. Here we describe next-generation sequencing studies leading to the determination of their complete genome sequences, and identification of both virus isolates as orbiviruses (family Reoviridae). Sequencing data showed that KVPTV has an AT-rich genome, whereas the genome of WMV is GC-rich. The size of the KVPTV genome is 18 234 nucleotides encoding proteins ranging 238-1290 amino acids (aa) in length. Similarly, the size of the WMV genome is 16 941 nucleotides encoding proteins ranging 214-1305 amino acids in length. Phylogenetic analysis of the VP1 gene, along with the capsid genes VP5 and VP7, revealed that KVPTV is likely a novel mosquito-borne virus and WMV is a tick-borne orbivirus. This study focuses on the phylogenetic comparison of these newly identified orbiviruses with mosquito-, tick- and Culicoides-borne orbiviruses isolated in India and other countries.

Pathogenicity, population genetics and dissemination of Bacillus anthracis

Bacillus anthracis, the etiological agent of anthrax, procures its particular virulence by a capsule and two AB type toxins: the lethal factor LF and the edema factor EF. These toxins primarily disable immune cells. Both toxins are translocated to the host cell by the adhesin-internalin subunit called protective antigen PA. PA enables LF to reach intra-luminal vesicles, where it remains active for long periods. Subsequently, LF translocates to non-infected cells, leading to inefficient late therapy of anthrax. B. anthracis undergoes slow evolution because it alternates between vegetative and long spore phases. Full genome sequence analysis of a large number of worldwide strains resulted in a robust evolutionary reconstruction of this bacterium, showing that B. anthracis is split in three main clades: A, B and C. Clade A efficiently disseminated worldwide underpinned by human activities including heavy intercontinental trade of goat and sheep hair. Subclade A.Br.WNA, which is widespread in the Northern American continent, is estimated to have split from clade A reaching the Northern American continent in the late Pleistocene epoch via the former Bering Land Bridge and further spread from Northwest southwards. An alternative hypothesis is that subclade A.Br.WNA. evolved from clade A.Br.TEA tracing it back to strains from Northern France that were assumingly dispatched by European explorers that settled along the St. Lawrence River. Clade B established mostly in Europe along the alpine axis where it evolved in association with local cattle breeds and hence displays specific geographic subclusters. Sequencing technologies are also used for forensic applications to trace unintended or criminal acts of release of B. anthracis. Under natural conditions, B. anthracis generally affects domesticated and wild ruminants in arid ecosystems. The more recently discovered B. cereus biovar anthracis spreads in tropical forests, where it threatens particularly endangered primate populations.

Genomic Comparison Among Global Isolates of L. interrogans Serovars Copenhageni and Icterohaemorrhagiae Identified Natural Genetic Variation Caused by an Indel

Leptospirosis is a worldwide zoonosis, responsible for more than 1 million cases and 60,000 deaths every year. Among the 13 pathogenic species of the genus Leptospira, serovars belonging to L. interrogans serogroup Icterohaemorrhagiae are considered to be the most virulent strains, and responsible for majority of the reported severe cases. Serovars Copenhageni and Icterohaemorrhagiae are major representatives of this serogroup and despite their public health relevance, little is known regarding the genetic differences between these two serovars. In this study, we analyzed the genome sequences of 67 isolates belonging to L. interrogans serovars Copenhageni and Icterohaemorrhagiae to investigate the influence of spatial and temporal variations on DNA sequence diversity. Out of the 1072 SNPs identified, 276 were in non-coding regions and 796 in coding regions. Indel analyses identified 258 indels, out of which 191 were found in coding regions and 67 in non-coding regions. Our phylogenetic analyses based on SNP dataset revealed that both serovars are closely related but showed distinct spatial clustering. However, likelihood ratio test of the indel data statistically confirmed the presence of a frameshift mutation within a homopolymeric tract of lic12008 gene (related to LPS biosynthesis) in all the L. interrogans serovar Icterohaemorrhagiae strains but not in the Copenhageni strains. Therefore, this internal indel identified can genetically distinguish L. interrogans serovar Copenhageni from serovar Icterohaemorrhagiae with high discriminatory power. To our knowledge, this is the first study to identify global sequence variations (SNPs and Indels) in L. interrogans serovars Copenhageni and Icterohaemorrhagiae.

Variant site strain typer (VaST): efficient strain typing using a minimal number of variant genomic sites

BACKGROUND

Targeted PCR amplicon sequencing (TAS) techniques provide a sensitive, scalable, and cost-effective way to query and identify closely related bacterial species and strains. Typically, this is accomplished by targeting housekeeping genes that provide resolution down to the family, genera, and sometimes species level. Unfortunately, this level of resolution is not sufficient in many applications where strain-level identification of bacteria is required (biodefense, forensics, clinical diagnostics, and outbreak investigations). Adding more genomic targets will increase the resolution, but the challenge is identifying the appropriate targets. VaST was developed to address this challenge by finding the minimum number of targets that, in combination, achieve maximum strain-level resolution for any strain complex. The final combination of target regions identified by the algorithm produce a unique haplotype for each strain which can be used as a fingerprint for identifying unknown samples in a TAS assay. VaST ensures that the targets have conserved primer regions so that the targets can be amplified in all of the known strains and it also favors the inclusion of targets with basal variants which makes the set more robust when identifying previously unseen strains.

RESULTS

We analyzed VaST's performance using a number of different pathogenic species that are relevant to human disease outbreaks and biodefense. The number of targets required to achieve full resolution ranged from 20 to 88% fewer sites than what would be required in the worst case and most of the resolution is achieved within the first 20 targets. We computationally and experimentally validated one of the VaST panels and found that the targets led to accurate phylogenetic placement of strains, even when the strains were not a part of the original panel design.

CONCLUSIONS

VaST is an open source software that, when provided a set of variant sites, can find the minimum number of sites that will provide maximum resolution of a strain complex, and it has many different run-time options that can accommodate a wide range of applications. VaST can be an effective tool in the design of strain identification panels that, when combined with TAS technologies, offer an efficient and inexpensive strain typing protocol.

A world without bacterial meningitis: how genomic epidemiology can inform vaccination strategy

Bacterial meningitis remains an important cause of global morbidity and mortality. Although effective vaccinations exist and are being increasingly used worldwide, bacterial diversity threatens their impact and the ultimate goal of eliminating the disease. Through genomic epidemiology, we can appreciate bacterial population structure and its consequences for transmission dynamics, virulence, antimicrobial resistance, and development of new vaccines. Here, we review what we have learned through genomic epidemiological studies, following the rapid implementation of whole genome sequencing that can help to optimise preventative strategies for bacterial meningitis.