Next-generation sequencing technologies and their application to the study and control of bacterial infections

Determination of Genomic Epidemiology of Historical Clostridium perfringens Outbreaks in New York State by Use of Two Web-Based Platforms: National Center for Biotechnology Information Pathogen Detection and FDA GalaxyTrakr

Clostridium perfringens is the second leading cause of bacterial foodborne illness in the United States. The Wadsworth Center (WC) at the New York State Department of Health enumerates infectious dose from primary patient and food samples and, until recently, identified C. perfringens to the species level only. We investigated whether whole-genome sequence-based subtyping could benefit epidemiological investigations of this pathogen, as it has with other enteric organisms. We retrospectively sequenced 76 patient and food samples received between May 2010 and February 2020, including 52 samples linked epidemiologically to 13 outbreaks and 24 sporadic samples not linked to other samples. Phylogenetic trees were built using two Web-based platforms: National Centers for Biotechnology Information Pathogen Detection (NCBI-PD) and GalaxyTrakr (a Galaxy instance supported by the GenomeTrakr initiative). For GalaxyTrakr analyses, single nucleotide polymorphism (SNP) matrices and maximum-likelihood (ML) trees were generated using 3 different reference genomes. Across the four separate analyses, phylogenetic clustering was generally concordant with epidemiologically identified outbreaks. SNP diversity among phylogenetically linked samples from an outbreak ranged from 0 to 20 SNPs, excepting one outbreak ranging from 4 to 62 SNPs. Importantly, four of the 13 outbreak isolates harbored one or more samples that were phylogenetic outliers, and for two outbreaks, no samples were closely related. Two specimens were found harboring two distinct genotypes. For samples below CDC enumeration dose threshold, phylogenetic clustering was robust and linked patient and/or food samples. We concluded that WGS phylogenetic clusters (i) are largely concordant with epidemiologically defined outbreaks, irrespective of analysis platform or reference genome we employed; (ii) have limited pairwise SNP diversity, allowing phylogenetic clusters to be distinguished from sporadic cases; and (iii) can aid in epidemiological investigations by identifying outlier and polyclonal samples.

Sensitive universal detection of blood parasites by selective pathogen-DNA enrichment and deep amplicon sequencing

BACKGROUND

Targeted amplicon deep sequencing (TADS) has enabled characterization of diverse bacterial communities, yet the application of TADS to communities of parasites has been relatively slow to advance. The greatest obstacle to this has been the genetic diversity of parasitic agents, which include helminths, protozoa, arthropods, and some acanthocephalans. Meanwhile, universal amplification of conserved loci from all parasites without amplifying host DNA has proven challenging. Pan-eukaryotic PCRs preferentially amplify the more abundant host DNA, obscuring parasite-derived reads following TADS. Flaherty et al. (2018) described a pan-parasitic TADS method involving amplification of eukaryotic 18S rDNA regions possessing restriction sites only in vertebrates. Using this method, host DNA in total DNA extracts could be selectively digested prior to PCR using restriction enzymes, thereby increasing the number of parasite-derived reads obtained following NGS. This approach showed promise though was only as sensitive as conventional PCR.

RESULTS

Here, we expand on this work by designing a second set of pan-eukaryotic primers flanking the priming sites already described, enabling nested PCR amplification of the established 18S rDNA target. This nested approach facilitated introduction of a second restriction digestion between the first and second PCR, reducing the proportional mass of amplifiable host-derived DNA while increasing the number of PCR amplification cycles. We applied this method to blood specimens containing Babesia, Plasmodium, various kinetoplastids, and filarial nematodes and confirmed its limit of detection (LOD) to be approximately 10-fold lower than previously described, falling within the range of most qPCR methods.

CONCLUSIONS

The assay detects and differentiates the major malaria parasites of humans, along with several other clinically important blood parasites. This represents an important step towards a TADS-based universal parasite diagnostic (UPDx) test with a sufficient LOD for routine applications. Video Abstract.

Subgingival microbiota in overweight and obese young adults with no destructive periodontal disease

BACKGROUND

This study analyzed the levels of a specific group of periodontal health/disease-related oral bacteria in the subgingival biofilm of young adults with overweight (OW) and obesity (OB), and no destructive periodontal disease.

METHODS

Full-mouth periodontal assessment and subgingival biofilm sampling were performed in individuals with normal weight (NW) (BMI [body mass index] ≥18.5 to ≤24.9 kg/m² ; n = 29), OW (BMI ≥25 to ≤29.9 kg/m² ; n = 26), or OB (BMI ≥30 kg/m² ; n = 22). BMI, waist (WC) and hip (HC) circumferences, and waist-hip ratio (WHR) were established for every individual. Biofilm samples were analyzed by checkerboard. Spearman coefficient, linear, and logistic regression analyses were obtained.

RESULTS

Gingivitis was detected in 45% NW, 65% OW, and 73% OB individuals. NW patients presented significantly less calculus and supragingival biofilm than OB. OW, and OB individuals had significantly higher levels of Porphyromonas gingivalis and Tannerella forsythia than NW patients (P <0.05). Treponema denticola correlated with BMI (rho = 0.31), WC (rho = 0.28), and HC (rho = 0.29), P≤0.01. Linear regression analysis showed significant (P <0.05) positive associations between BMI, WC, HC, and WHR indicators and Prevotella spp., Lactobacillus spp., V. parvula, and A. actinomycetemcomitans (Aa); negative associations were found between Capnocytophaga spp., WC, and HC (β = -0.29 and β = -0.37, respectively; P <0.01). However, the interaction of Prevotella spp. and T. forsythia decreased the likelihood of an individual to be diagnosed as OW/OB (OR 0.183 [95% CI, 0.062-0.540]).

CONCLUSIONS

Few periodontal pathogens differed in levels between NW and OW/OB individuals without destructive periodontal disease. Moreover, Aa, T. denticola, and Prevotella spp. were associated with clinical parameters of obesity.

Determining the serotype composition of mixed samples of pneumococcus using whole-genome sequencing

Serotyping of Streptococcus pneumoniae is a critical tool in the surveillance of the pathogen and in the development and evaluation of vaccines. Whole-genome DNA sequencing and analysis is becoming increasingly common and is an effective method for pneumococcal serotype identification of pure isolates. However, because of the complexities of the pneumococcal capsular loci, current analysis software requires samples to be pure (or nearly pure) and only contain a single pneumococcal serotype. We introduce a new software tool called SeroCall, which can identify and quantitate the serotypes present in samples, even when several serotypes are present. The sample preparation, library preparation and sequencing follow standard laboratory protocols. The software runs as fast as or faster than existing identification tools on typical computing servers and is freely available under an open source licence at https://github.com/knightjimr/serocall. Using samples with known concentrations of different serotypes as well as blinded samples, we were able to accurately quantify the abundance of different serotypes of pneumococcus in mixed cultures, with 100 % accuracy for detecting the major serotype and up to 86 % accuracy for detecting minor serotypes. We were also able to track changes in serotype frequency over time in an experimental setting. This approach could be applied in both epidemiological field studies of pneumococcal colonization and experimental laboratory studies, and could provide a cheaper and more efficient method for serotyping than alternative approaches.

Genomic Analysis of Antimicrobial Resistance Genotype-to-Phenotype Agreement in Helicobacter pylori

Antimicrobial resistance (AMR) in Helicobacter pylori is increasing and can result in treatment failure and inappropriate antibiotic usage. This study used whole genome sequencing (WGS) to comprehensively analyze the H. pylori resistome and phylogeny in order to characterize Israeli H. pylori. Israeli H. pylori isolates (n = 48) underwent antimicrobial susceptibility testing (AST) against five antimicrobials and WGS analysis. Literature review identified 111 mutations reported to correlate with phenotypic resistance to these antimicrobials. Analysis was conducted via our in-house bioinformatics pipeline targeting point mutations in the relevant genes (pbp1A, 23S rRNA, gyrA, rdxA, frxA, and rpoB) in order to assess genotype-to-phenotype correlation. Resistance rates of study isolates were as follows: clarithromycin 54%, metronidazole 31%, amoxicillin 10%, rifampicin 4%, and levofloxacin 2%. Genotype-to-phenotype correlation was inconsistent; for every analyzed gene at least one phenotypically susceptible isolate was found to have a mutation previously associated with resistance. This was also observed regarding mutations commonly used in commercial kits to diagnose AMR in H. pylori cases. Furthermore, 11 novel point mutations associated with a resistant phenotype were detected. Analysis of a unique set of H. pylori isolates demonstrates that inferring resistance phenotypes from WGS in H. pylori remains challenging and should be optimized further.

Assessing Nanopore Sequencing for Clinical Diagnostics: a Comparison of Next-Generation Sequencing (NGS) Methods for Mycobacterium tuberculosis

Next-generation sequencing technologies are being rapidly adopted as a tool of choice for diagnostic and outbreak investigation in public health laboratories. However, costs of operation and the need for specialized staff remain major hurdles for laboratories with limited resources for implementing these technologies. This project aimed to assess the feasibility of using Oxford Nanopore MinION whole-genome sequencing data of Mycobacterium tuberculosis isolates for species identification, in silico spoligotyping, detection of mutations associated with antimicrobial resistance (AMR) to accurately predict drug susceptibility profiles, and phylogenetic analysis to detect transmission between cases. The results were compared prospectively in real time to those obtained with our current clinically validated Illumina MiSeq sequencing assay for M. tuberculosis and phenotypic drug susceptibility testing results when available. Our assessment of 431 sequenced samples over a 32-week period demonstrates that, when using the proper quality controls and thresholds, the MinION can achieve levels of genotyping analysis and phenotypic resistance predictions comparable to those of the Illumina MiSeq at a very competitive cost per sample. Our results indicate that nanopore sequencing can be a suitable alternative to, or complement, currently used sequencing platforms in a clinical setting and has the potential to be widely adopted in public health laboratories in the near future.

Evaluation of High-Throughput Next-Generation Sequencing Applied in the Pathogenic Diagnosis of Bloodstream Infections

Background: Bloodstream infection (BSI) has been one of the biggest headaches for clinicians, as it not only aggravates symptoms but also increases the length of stay, the cost of hospitalization, and the side effects caused by antibiotics. It is an urgent need for clinicians to develop timely and accurate methods to find microorganisms. Currently, the gold standard for diagnosing BSI is blood culture, but it takes three to eight days to produce results, and its positive rate is extremely low. Next-generation sequencing (NGS) has emerged as a better technology desperately needed by doctors and patients to diagnose BSI. Objectives: This study compared NGS and blood culture methods in clinical patients with BSI. Methods: In this study, blood culture and NGS were used to analyze the blood of patients with BSI in different departments of the First Affiliated Hospital of Kunming Medical University. Results: Next-generation sequencing detected 60 pathogens in 63 blood samples, while blood culture detected 15 pathogens in 336 blood samples from 63 patients who were clinically considered to be infected. Pathogens detected by NGS included bacteria, fungi, and viruses, while blood culture only found bacteria and fungi. The positive rates of blood culture diagnosis and NGS diagnosis in BSI patients were 23.8% (15/63) (CI: 13.3% - 34.3%) and 95% (60/63) (CI: 90% - 100%), respectively. Conclusions: Our results showed that NGS creates a new diagnostic platform for patients with BSI. Its wide detection range, high positive rate, and characteristics of rapid detection will benefit patients with BSI.

Sources and transmission routes of campylobacteriosis: A combined analysis of genome and exposure data

OBJECTIVES

To determine the contributions of several animal and environmental sources of human campylobacteriosis and identify source-specific risk factors.

METHODS

1417 Campylobacter jejuni/coli isolates from the Netherlands in 2017-2019 were whole-genome sequenced, including isolates from human cases (n = 280), chickens/turkeys (n = 238), laying hens (n = 56), cattle (n = 158), veal calves (n = 49), sheep/goats (n = 111), pigs (n = 110), dogs/cats (n = 100), wild birds (n = 62), and surface water (n = 253). Questionnaire-based exposure data was collected. Source attribution was performed using core-genome multilocus sequence typing. Risk factors were determined on the attribution estimates.

RESULTS

Cases were mostly attributed to chickens/turkeys (48.2%), dogs/cats (18.0%), cattle (12.1%), and surface water (8.5%). Of the associations identified, never consuming chicken, as well as frequent chicken consumption, and rarely washing hands after touching raw meat, were risk factors for chicken/turkey-attributable infections. Consuming unpasteurized milk or barbecued beef increased the risk for cattle-attributable infections. Risk factors for infections attributable to environmental sources were open water swimming, contact with dog faeces, and consuming non-chicken/turkey avian meat like game birds.

CONCLUSIONS

Poultry and cattle are the main livestock sources of campylobacteriosis, while pets and surface water are important non-livestock sources. Foodborne transmission is only partially consistent with the attributions, as frequency and alternative pathways of exposure are significant.

Validation and interpretation of IGH and TCR clonality testing by Ion Torrent S5 NGS for diagnosis and disease monitoring in B and T cell cancers

Cancers of B and T lymphocytes are the most common hematologic malignancies in the US. Molecular assays for assessing clonal rearrangements of the immunoglobulin receptor (IGH) and T-cell receptor (TCR), commonly referred to as B- and T-cell clonality, as well as determination of IGH somatic mutation status, enables improved diagnostic accuracy and disease monitoring. Here we describe validation of NGS LymphoTrack (IGH, TCRG, Invivoscribe, Inc) with Ion Torrent S5 sequencing, which employs a different sequencing chemistry and has not been previously reported for NGS clonality to our knowledge. We also demonstrate the concordance of clonality by LymphoTrack with S5 sequencing with other molecular methodologies and with clinical measurements of disease. We show that LymphoTrack with S5 sequencing identifies previously detected IGH and TCRG clonal sequences across matched biopsy specimens and clinical timepoints, enabling more precise and sensitive disease monitoring for B- and T-cell cancers compared to PCR fragment or capillary sequencing. In sum, our study demonstrates that the LymphoTrack assays with Ion Torrent S5 sequencing 1) can be used successfully for IGH and TCR clonality with reproducible results; 2) generates and quantifies clonal sequences to enable highly precise comparison of samples; 3) are substantially more sensitive than PCR fragment and return clonality results in specimens that failed PCR fragment assays; and 4) the TCRG assays are highly concordant with clinical and histopathologic diagnoses. Taken together, the LymphoTrack with Ion S5 NGS clonality assays offer a sensitive and precise method for diagnostic testing and disease monitoring in B- and T-cell cancers.

Use of Oxford Nanopore MinION to generate full-length sequences of the Blastocystis small subunit (SSU) rRNA gene

Background

Blastocystis sp. is one of the most common enteric parasites of humans and animals worldwide. It is well recognized that this ubiquitous protist displays a remarkable degree of genetic diversity in the SSU rRNA gene, which is currently the main gene used for defining Blastocystis subtypes. Yet, full-length reference sequences of this gene are available for only 16 subtypes of Blastocystis in part because of the technical difficulties associated with obtaining these sequences from complex samples.

Methods

We have developed a method using Oxford Nanopore MinION long-read sequencing and universal eukaryotic primers to produce full-length (> 1800 bp) SSU rRNA gene sequences for Blastocystis. Seven Blastocystis specimens representing five subtypes (ST1, ST4, ST10, ST11, and ST14) obtained both from cultures and feces were used for validation.

Results

We demonstrate that this method can be used to produce highly accurate full-length sequences from both cultured and fecal DNA isolates. Full-length sequences were successfully obtained from all five subtypes including ST11 for which no full-length reference sequence currently exists and for an isolate that contained mixed ST10/ST14.

Conclusions

The suitability of the use of MinION long-read sequencing technology to successfully generate full-length Blastocystis SSU rRNA gene sequences was demonstrated. The ability to produce full-length SSU rRNA gene sequences is key in understanding the role of genetic diversity in important aspects of Blastocystis biology such as transmission, host specificity, and pathogenicity.

Currently Applied Molecular Assays for Identifying ESR1 Mutations in Patients with Advanced Breast Cancer

Approximately 70% of breast cancers, the leading cause of cancer-related mortality worldwide, are positive for the estrogen receptor (ER). Treatment of patients with luminal subtypes is mainly based on endocrine therapy. However, ER positivity is reduced and ESR1 mutations play an important role in resistance to endocrine therapy, leading to advanced breast cancer. Various methodologies for the detection of ESR1 mutations have been developed, and the most commonly used method is next-generation sequencing (NGS)-based assays (50.0%) followed by droplet digital PCR (ddPCR) (45.5%). Regarding the sample type, tissue (50.0%) was more frequently used than plasma (27.3%). However, plasma (46.2%) became the most used method in 2016-2019, in contrast to 2012-2015 (22.2%). In 2016-2019, ddPCR (61.5%), rather than NGS (30.8%), became a more popular method than it was in 2012-2015. The easy accessibility, non-invasiveness, and demonstrated usefulness with high sensitivity of ddPCR using plasma have changed the trends. When using these assays, there should be a comprehensive understanding of the principles, advantages, vulnerability, and precautions for interpretation. In the future, advanced NGS platforms and modified ddPCR will benefit patients by facilitating treatment decisions efficiently based on information regarding ESR1 mutations.

A photo-sensitizable phage for multidrug-resistant Acinetobacter baumannii therapy and biofilm ablation

Antibiotic abuse causes the emergence of bacterial resistance. Photodynamic antibacterial chemotherapy (PACT) has great potential to solve serious bacterial resistance, but it suffers from the inefficient generation of ROS and the lack of bacterial targeting ability. Herein, a unique cationic photosensitizer (NB) and bacteriophage (ABP)-based photodynamic antimicrobial agent (APNB) is developed for precise bacterial eradication and efficient biofilm ablation. Thanks to the structural modification of the NB photosensitizer with a sulfur atom, it displays excellent reactive oxygen species (ROS)-production ability. Moreover, specific binding to pathogenic microorganisms can be provided by bacteriophages. The developed APNB has multiple functions, including bacteria targeting, near-infrared fluorescence imaging and combination therapy (PACT and phage therapy). Both in vitro and in vivo experiments prove that APNB can efficiently treat A. baumannii infection. Particularly, the recovery from A. baumannii infection after APNB treatment is faster than that with ampicillin and polymyxin B in vivo. Furthermore, the strategy of combining bacteriophages and photosensitizers is employed to eradicate bacterial biofilms for the first time, and it shows the excellent biofilm ablation effect as expected. Thus, APNB has huge potential in fighting against multidrug-resistant bacteria and biofilm ablation in practice.

APNB for multidrug-resistant A. Baumannii therapy and biofilms ablation.

Identification of Clinically Relevant Streptococcus and Enterococcus Species Based on Biochemical Methods and 16S rRNA, sodA, tuf, rpoB, and recA Gene Sequencing

Streptococci and enterococci are significant opportunistic pathogens in epidemiology and infectious medicine. High genetic and taxonomic similarities and several reclassifications within genera are the most challenging in species identification. The aim of this study was to identify Streptococcus and Enterococcus species using genetic and phenotypic methods and to determine the most discriminatory identification method. Thirty strains recovered from clinical samples representing 15 streptococcal species, five enterococcal species, and four nonstreptococcal species were subjected to bacterial identification by the Vitek^® 2 system and Sanger-based sequencing methods targeting the 16S rRNA, sodA, tuf, rpoB, and recA genes. Phenotypic methods allowed the identification of 10 streptococcal strains, five enterococcal strains, and four nonstreptococcal strains (Leuconostoc, Granulicatella, and Globicatella genera). The combination of sequencing methods allowed the identification of 21 streptococcal strains, five enterococcal strains, and four nonstreptococcal strains. The 16S rRNA and rpoB genes had the highest identification potential. Only a combination of several molecular methods was sufficient for unambiguous confirmation of species identity. This study will be useful for comparison of several identification methods, both those used as a first choice in routine microbiology and those used for final confirmation.

What Do Students in Pharmacy and Medicine Think About Pharmacogenomics and Personalized Medicine Education? Awareness, Attitudes, and Perceptions in Malaysian Health Sciences

This study reports on the attitudes and perceptions toward pharmacogenomics (PGx) and personalized medicine (PM) education among pharmacy and medical students in Malaysian health sciences. Importantly, the survey was developed through a codesign approach, with field pretesting/design with users before the actual survey, and based on collaboration between institutions in Greece and Malaysia. The study addressed eight key areas of interest to education in health sciences: (1) General awareness about genetics and PGx, (2) Attitude toward genetic testing usefulness, (3) Benefits of direct-to-consumer personal genome testing as a "diagnostic" tool, (4) Concerns (risks) about genetics, (5) Effectiveness of genetic testing in PM, (6) Benefits of PGx on disease management, (7) Benefits of PGx on drug management, and (8) Attitudes toward genetic testing public endorsement. We observed that Malaysian students appear aware of the term PGx, but there are areas of critical knowledge gap such as the need for greater familiarity with the concept of PGx implementation science, and the availability of genetic testing in clinical practice. This is one of the first studies on perceptions and attitudes toward PGx testing in Southeast Asia. The present findings provide a map of the views and perspectives of medicine and pharmacy students regarding PGx and implementation of PM in Malaysia and should assist toward facilitating the integration of genomics into the medical decision-making process. To this end, it is necessary to enhance collaboration between universities, health care institutions, and governing bodies to incorporate further training and additional education topics related to PGx and genetic testing. This is the first study that assesses the level of PGx and genomics knowledge of pharmacy and medicine students in Southeast Asia, Malaysia in particular, and thus paves the way to guide future global PGx implementation science.

Transcriptomics in Trichoderma reesei

Transcriptomics is a powerful technique to study gene expression. The main purpose of transcriptome studies in the filamentous fungus Trichoderma reesei is the analysis of differentially expressed genes as a transcriptional response of the genome to different environmental stimuli or physiological conditions such as sugar availability, nitrogen metabolism, pH response, and oxidative stress, among others. Here we describe the full protocol of RNA sequencing methodology from RNA isolation to data analysis in order to access the T. reesei transcriptome.

Next Generation Sequencing and Bioinformatics Analysis of Family Genetic Inheritance

Mendelian and complex genetic trait diseases continue to burden and affect society both socially and economically. The lack of effective tests has hampered diagnosis thus, the affected lack proper prognosis. Mendelian diseases are caused by genetic mutations in a singular gene while complex trait diseases are caused by the accumulation of mutations in either linked or unlinked genomic regions. Significant advances have been made in identifying novel diseases associated mutations especially with the introduction of next generation and third generation sequencing. Regardless, some diseases are still without diagnosis as most tests rely on SNP genotyping panels developed from population based genetic analyses. Analysis of family genetic inheritance using whole genomes, whole exomes or a panel of genes has been shown to be effective in identifying disease-causing mutations. In this review, we discuss next generation and third generation sequencing platforms, bioinformatic tools and genetic resources commonly used to analyze family based genomic data with a focus on identifying inherited or novel disease-causing mutations. Additionally, we also highlight the analytical, ethical and regulatory challenges associated with analyzing personal genomes which constitute the data used for family genetic inheritance.

Full Transcriptome Analysis of Callus Suspension Culture System of Bletilla striata

Background

Bletilla striata has been widely used in the pharmacology industry. To effectively produce the secondary metabolites through suspension cultured cells of B. striata, it is important to exploring the full-length transcriptome data and the genes related to cell growth and chemical producing of all culture stages. We applied a combination of Real-Time Sequencing of Single Molecule (SMRT) and second-generation sequencing (SGS) to generate the complete and full-length transcriptome of B. striata suspension cultured cells.

Methods

The B. striata transcriptome was formed in de novo way by using PacBio isoform sequencing (Iso-Seq) on a pooled RNA sample derived from 23 samples of 10 culture stages, to explore the potential for capturing full-length transcript isoforms. All unigenes were obtained after splicing, assembling, and clustering, and corrected by the SGS results. The obtained unigenes were compared with the databases, and the functions were annotated and classified.

Results and conclusions

A total of 100,276 high-quality full-length transcripts were obtained, with an average length of 2530 bp and an N50 of 3302 bp. About 52% of total sequences were annotated against the Gene Ontology, 53,316 unigenes were hit by KOG annotations and divided into 26 functional categories, 80,020 unigenes were mapped by KEGG annotations and clustered into 363 pathways. Furthermore, 15,133 long-chain non-coding RNAs (lncRNAs) were detected. And 68,996 coding sequences were identified based on SSR analysis, among which 31 pairs of primers selected at random were amplified and obtained stable bands. In conclusion, our results provide new full-length transcriptome data and genetic resources for identifying growth and metabolism-related genes, which provide a solid foundation for further research on its growth regulation mechanisms and genetic engineering breeding mechanisms of B. striata.

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.

Emergence of highly pathogenic H5N2 and H7N1 influenza A viruses from low pathogenic precursors by serial passage in ovo

Highly pathogenic (HPAI) strains emerge from their low pathogenic (LPAI) precursors and cause severe disease in poultry with enormous economic losses, and zoonotic potential. Understanding the mechanisms involved in HPAI emergence is thus an important goal for risk assessments. In this study ostrich-origin H5N2 and H7N1 LPAI progenitor viruses were serially passaged seventeen times in 14-day old embryonated chicken eggs and Ion Torrent ultra-deep sequencing was used to monitor the incremental changes in the consensus genome sequences. Both virus strains increased in virulence with successive passages, but the H7N1 virus attained a virulent phenotype sooner. Mutations V63M, E228V and D272G in the HA protein, Q357K in the nucleoprotein (NP) and H155P in the neuraminidase protein correlated with the increased pathogenicity of the H5N2 virus; whereas R584H and L589I substitutions in the polymerase B2 protein, A146T and Q220E in HA plus D231N in the matrix 1 protein correlated with increased pathogenicity of the H7N1 virus in embryos. Enzymatic cleavage of HA protein is the critical virulence determinant, and HA cleavage site motifs containing multibasic amino acids were detected at the sub-consensus level. The motifs PQERRR/GLF and PQRERR/GLF were first detected in passages 11 and 15 respectively of the H5N2 virus, and in the H7N1 virus the motifs PELPKGKK/GLF and PELPKRR/GLF were detected as early as passage 7. Most significantly, a 13 nucleotide insert of unknown origin was identified at passage 6 of the H5N2 virus, and at passage 17 a 42 nucleotide insert derived from the influenza NP gene was identified. This is the first report of non-homologous recombination at the HA cleavage site in an H5 subtype virus. This study provides insights into how HPAI viruses emerge from low pathogenic precursors and demonstrated the pathogenic potential of H5N2 and H7N1 strains that have not yet been implicated in HPAI outbreaks.

Translational biomarkers in the era of precision medicine

In this chapter we discuss the past, present and future of clinical biomarker development. We explore the advent of new technologies, paving the way in which health, medicine and disease is understood. This review includes the identification of physicochemical assays, current regulations, the development and reproducibility of clinical trials, as well as, the revolution of omics technologies and state-of-the-art integration and analysis approaches.

Comparison of Molecular Subtyping and Antimicrobial Resistance Detection Methods Used in a Large Multistate Outbreak of Extensively Drug-Resistant Campylobacter jejuni Infections Linked to Pet Store Puppies

Campylobacter jejuni is a leading cause of enteric bacterial illness in the United States. Traditional molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE) and 7-gene multilocus sequence typing (MLST), provided limited resolution to adequately identify C. jejuni outbreaks and separate out sporadic isolates during outbreak investigations. Whole-genome sequencing (WGS) has emerged as a powerful tool for C. jejuni outbreak detection. In this investigation, 45 human and 11 puppy isolates obtained during a 2016-2018 outbreak linked to pet store puppies were sequenced. Core genome multilocus sequence typing (cgMLST) and high-quality single nucleotide polymorphism (hqSNP) analysis of the sequence data separated the isolates into the same two clades containing minor within-clade differences; however, cgMLST analysis does not require selection of an appropriate reference genome, making the method preferable to hqSNP analysis for Campylobacter surveillance and cluster detection. The isolates were classified as sequence type 2109 (ST2109)-a rarely seen MLST sequence type. PFGE was performed on 38 human and 10 puppy isolates; PFGE patterns did not reliably predict clustering by cgMLST analysis. Genetic detection of antimicrobial resistance determinants predicted that all outbreak-associated isolates would be resistant to six drug classes. Traditional antimicrobial susceptibility testing (AST) confirmed a high correlation between genotypic and phenotypic antimicrobial resistance determinations. WGS analysis linked C. jejuni isolates in humans and pet store puppies even when canine exposure information was unknown, aiding the epidemiological investigation during the outbreak. WGS data were also used to quickly identify the highly drug-resistant profile of these outbreak-associated C. jejuni isolates.

Metagenomic Next-Generation Sequencing Improves Diagnosis of Osteoarticular Infections From Abscess Specimens: A Multicenter Retrospective Study

Background: We conducted this retrospective study to reveal the accuracy of metagenomic next-generation sequencing (mNGS) for diagnosing osteoarticular infections from fresh abscess specimens obtained from patients in an HIV-naive population.

Methods: We retrospectively analyzed hospital records at three participating TB-specialized hospitals for patients admitted with suggestive diagnoses of osteoarticular tuberculosis between January 2018 and August 2019. Abscess specimens obtained from each patient were tested via pathogen culture, GeneXpert Mycobacterium tuberculosis (MTB)/rifampicin (RIF), and mNGS assay.

Results: A total of 82 abscess samples were collected from patients with osteoarticular infections, including 53 cases with (64.6%) bacterial, 21 (25.6%) with mycobacterial, 7 (8.5%) with fungal, and 1 (1.2%) with actinomycetal organisms detected. Analysis of mNGS assay results identified potential pathogens in all cases, with M. tuberculosis complex (MTBC) most frequently isolated, followed by Staphylococcus aureus and Brucella melitensis. Conventional culture testing identified causative pathogens in only 48.4% of samples, a significantly lower rate than the mNGS pathogen identification rate (100%, p < 0.01). Culture-positive group specimens yielded significantly greater numbers of sequence reads than did culture-negative group specimens (p < 0.01). Of patients receiving surgical interventions and mNGS-guided treatment, 76 (92.7%) experienced favorable outcomes by the time of follow-up assessment at 3 months post-treatment. Notably, MTBC detection in two patients experiencing treatment failure suggests that they had mixed infections with MTBC and other pathogens.

Conclusion: Results presented here demonstrate that mNGS has a greater pathogen detection rate in osteoarticular infections than conventional culture-based methods.

Benchmarking hybrid assembly approaches for genomic analyses of bacterial pathogens using Illumina and Oxford Nanopore sequencing

Background

We benchmarked the hybrid assembly approaches of MaSuRCA, SPAdes, and Unicycler for bacterial pathogens using Illumina and Oxford Nanopore sequencing by determining genome completeness and accuracy, antimicrobial resistance (AMR), virulence potential, multilocus sequence typing (MLST), phylogeny, and pan genome. Ten bacterial species (10 strains) were tested for simulated reads of both mediocre- and low-quality, whereas 11 bacterial species (12 strains) were tested for real reads.

Results

Unicycler performed the best for achieving contiguous genomes, closely followed by MaSuRCA, while all SPAdes assemblies were incomplete. MaSuRCA was less tolerant of low-quality long reads than SPAdes and Unicycler. The hybrid assemblies of five antimicrobial-resistant strains with simulated reads provided consistent AMR genotypes with the reference genomes. The MaSuRCA assembly of Staphylococcus aureus with real reads contained msr(A) and tet(K), while the reference genome and SPAdes and Unicycler assemblies harbored blaZ. The AMR genotypes of the reference genomes and hybrid assemblies were consistent for the other five antimicrobial-resistant strains with real reads. The numbers of virulence genes in all hybrid assemblies were similar to those of the reference genomes, irrespective of simulated or real reads. Only one exception existed that the reference genome and hybrid assemblies of Pseudomonas aeruginosa with mediocre-quality long reads carried 241 virulence genes, whereas 184 virulence genes were identified in the hybrid assemblies of low-quality long reads. The MaSuRCA assemblies of Escherichia coli O157:H7 and Salmonella Typhimurium with mediocre-quality long reads contained 126 and 118 virulence genes, respectively, while 110 and 107 virulence genes were detected in their MaSuRCA assemblies of low-quality long reads, respectively. All approaches performed well in our MLST and phylogenetic analyses. The pan genomes of the hybrid assemblies of S. Typhimurium with mediocre-quality long reads were similar to that of the reference genome, while SPAdes and Unicycler were more tolerant of low-quality long reads than MaSuRCA for the pan-genome analysis. All approaches functioned well in the pan-genome analysis of Campylobacter jejuni with real reads.

Conclusions

Our research demonstrates the hybrid assembly pipeline of Unicycler as a superior approach for genomic analyses of bacterial pathogens using Illumina and Oxford Nanopore sequencing.

Cost-effectiveness analysis comparing companion diagnostic tests for EGFR, ALK, and ROS1 versus next-generation sequencing (NGS) in advanced adenocarcinoma lung cancer patients

BACKGROUND

The treatment of choice for advanced non-small cell lung cancer is selected according to the presence of specific alterations. Patients should undergo molecular testing for relevant modifications and the mutational status of EGFR and translocation of ALK and ROS1 are commonly tested to offer the best intervention. In addition, the tests costs should also be taken in consideration. Therefore, this work was performed in order to evaluate the cost-effectiveness of a unique exam using NGS (next generation sequencing) versus other routinely used tests which involve RT-PCR and FISH.

METHODS

The target population was NSCLC, adenocarcinoma, and candidates to first-line therapy. Two strategies were undertaken, strategy 1 corresponded to sequential tests with EGFR RT-PCR, then FISH for ALK and ROS1. Strategy 2 differed from 1 in that ALK and ROS1 translocation testing were performed simultaneously by FISH. Strategy 3 considered single test next-generation sequencing, a platform that includes EGFR, ALK and ROS1 genes. A decision tree analysis was used to model genetic testing options. From the test results, a microsimulation model was nested to estimate survival outcomes and costs of therapeutic options.

RESULTS

The use of NGS added 24% extra true cases as well as extra costs attributed to the molecular testing. The ICER comparing NGS with sequential tests was US$ 3479.11/correct case detected. The NGS improved a slight gain in life years and QALYs.

CONCLUSION

Our results indicated that, although precise, the molecular diagnosis by NGS of patients with advanced stage NSCLC adenocarcinoma histology was not cost-effective in terms of quality-adjusted life years from the perspective of the Brazilian supplementary health system.

Synthesizing Systems Biology Knowledge from Omics Using Genome-Scale Models

Omic technologies have enabled the complete readout of the molecular state of a cell at different biological scales. In principle, the combination of multiple omic data types can provide an integrated view of the entire biological system. This integration requires appropriate models in a systems biology approach. Here, genome-scale models (GEMs) are focused upon as one computational systems biology approach for interpreting and integrating multi-omic data. GEMs convert the reactions (related to metabolism, transcription, and translation) that occur in an organism to a mathematical formulation that can be modeled using optimization principles. A variety of genome-scale modeling methods used to interpret multiple omic data types, including genomics, transcriptomics, proteomics, metabolomics, and meta-omics are reviewed. The ability to interpret omics in the context of biological systems has yielded important findings for human health, environmental biotechnology, bioenergy, and metabolic engineering. The authors find that concurrent with advancements in omic technologies, genome-scale modeling methods are also expanding to enable better interpretation of omic data. Therefore, continued synthesis of valuable knowledge, through the integration of omic data with GEMs, are expected.

MDACP: A Pathogen Genome and Metagenome Analysis Cloud Platform

Pathogenic microorganism analysis based on next-generation sequencing technology is an important tool for clinical diagnosis, public health surveillance, and outbreak investigation. However, scientific researchers without the relevant background lack the time, training, or infrastructure to use large data sets or install and use command line tools. Therefore, the bioinformatic team at the Chinese Center for Disease Control and Prevention developed the Microbial Data Analysis Cloud Platform (MDACP) as a safe, professional, and efficient pathogen genetic data analysis platform for rapid microbial data mining, such as for candidate pathogen detection, genome typing, and traceability. MDACP is a web service system based on the Docker platform and can be used for data analysis on various operating systems. The platform focuses on pathogen analysis and continuously develops new analysis processes according to the analysis needs of the users. This platform has a friendly user interface and is easy to operate, allowing users to submit data through data pages or graphical clients, flexibly control parameters according to data conditions, and analyze data in parallel with multiple tasks. Researchers can quickly carry out bioinformatic analyses without coding work, promote follow-up research and information mining of projects, and improve the utilization of big data in the field of disease control. MDACP enables research personnel to conduct data analysis and management and assists clinicians and disease control personnel with mining information, such as pathogen identification, classification, and traceability.

Perceived utility and feasibility of pathogen genomics for public health practice: a survey among public health professionals working in the field of infectious diseases, Belgium, 2019

BACKGROUND

Pathogen genomics is increasingly being translated from the research setting into the activities of public health professionals operating at different levels. This survey aims to appraise the literacy level and gather the opinions of public health experts and allied professionals working in the field of infectious diseases in Belgium concerning the implementation of next-generation sequencing (NGS) in public health practice.

METHODS

In May 2019, Belgian public health and healthcare professionals were invited to complete an online survey containing eight main topics including background questions, general attitude towards pathogen genomics for public health practice and main concerns, genomic literacy, current and planned NGS activities, place of NGS in diagnostic microbiology pathways, data sharing obstacles, end-user requirements, and key drivers for the implementation of NGS. Descriptive statistics were used to report on the frequency distribution of multiple choice responses whereas thematic analysis was used to analyze free text responses. A multivariable logistic regression model was constructed to identify important predictors for a positive attitude towards the implementation of pathogen genomics in public health practice.

RESULTS

146 out of the 753 invited public health professionals completed the survey. 63% of respondents indicated that public health agencies should be using genomics to understand and control infectious diseases. Having a high level of expertise in the field of pathogen genomics was the strongest predictor of a positive attitude (OR = 4.04, 95% CI = 1.11 - 17.23). A significantly higher proportion of data providers indicated to have followed training in the field of pathogen genomics compared to data end-users (p < 0.001). Overall, 79% of participants expressed interest in receiving further training. Main concerns were related to the cost of sequencing technologies, data sharing, data integration, interdisciplinary working, and bioinformatics expertise.

CONCLUSIONS

Belgian health professionals expressed favorable views about implementation of pathogen genomics in their work activities related to infectious disease surveillance and control. They expressed the need for suitable training initiatives to strengthen their competences in the field. Their perception of the utility and feasibility of pathogen genomics for public health purposes will be a key driver for its further implementation.

NanoReviser: An Error-Correction Tool for Nanopore Sequencing Based on a Deep Learning Algorithm

Nanopore sequencing is regarded as one of the most promising third-generation sequencing (TGS) technologies. Since 2014, Oxford Nanopore Technologies (ONT) has developed a series of devices based on nanopore sequencing to produce very long reads, with an expected impact on genomics. However, the nanopore sequencing reads are susceptible to a fairly high error rate owing to the difficulty in identifying the DNA bases from the complex electrical signals. Although several basecalling tools have been developed for nanopore sequencing over the past years, it is still challenging to correct the sequences after applying the basecalling procedure. In this study, we developed an open-source DNA basecalling reviser, NanoReviser, based on a deep learning algorithm to correct the basecalling errors introduced by current basecallers provided by default. In our module, we re-segmented the raw electrical signals based on the basecalled sequences provided by the default basecallers. By employing convolution neural networks (CNNs) and bidirectional long short-term memory (Bi-LSTM) networks, we took advantage of the information from the raw electrical signals and the basecalled sequences from the basecallers. Our results showed NanoReviser, as a post-basecalling reviser, significantly improving the basecalling quality. After being trained on standard ONT sequencing reads from public E. coli and human NA12878 datasets, NanoReviser reduced the sequencing error rate by over 5% for both the E. coli dataset and the human dataset. The performance of NanoReviser was found to be better than those of all current basecalling tools. Furthermore, we analyzed the modified bases of the E. coli dataset and added the methylation information to train our module. With the methylation annotation, NanoReviser reduced the error rate by 7% for the E. coli dataset and specifically reduced the error rate by over 10% for the regions of the sequence rich in methylated bases. To the best of our knowledge, NanoReviser is the first post-processing tool after basecalling to accurately correct the nanopore sequences without the time-consuming procedure of building the consensus sequence. The NanoReviser package is freely available at https://github.com/pkubioinformatics/NanoReviser.

Bacterial Vaginosis: Current Diagnostic Avenues and Future Opportunities

A healthy female genital tract harbors a microbiome dominated by lactic acid and hydrogen peroxide producing bacteria, which provide protection against infections by maintaining a low pH. Changes in the bacterial compositions of the vaginal microbiome can lead to bacterial vaginosis (BV), which is often associated with vaginal inflammation. Bacterial vaginosis increases the risk of acquiring sexually transmitted infections (STIs) like human immunodeficiency virus (HIV) and affects women's reproductive health negatively. In pregnant women, BV can lead to chorioamnionitis and adverse pregnancy outcomes, including preterm premature rupture of the membranes and preterm birth. In order to manage BV effectively, good diagnostic procedures are required. Traditionally clinical and microscopic methods have been used to diagnose BV; however, these methods require skilled staff and time and suffer from reduced sensitivity and specificity. New diagnostics, including highly sensitive and specific point-of-care (POC) tests, treatment modalities and vaccines can be developed based on the identification of biomarkers from the growing pool of vaginal microbiome and vaginal metabolome data. In this review the current and future diagnostic avenues will be discussed.

Precise Species Identification for Enterobacter: a Genome Sequence-Based Study with Reporting of Two Novel Species, Enterobacter quasiroggenkampii sp. nov. and Enterobacter quasimori sp. nov

Enterobacter species are major human pathogens. Precise species identification lays a foundation for microbiology, but the taxonomy of Enterobacter is complicated and confusing. In this study, first, we significantly updated the taxonomy of Enterobacter by rigorous genome analyses and found that all subspecies assignments of Enterobacter were incorrect. Second, we characterized and reported two novel Enterobacter species with clinical significance. Third, we curated 1,997 Enterobacter genome sequences deposited in GenBank and found that the species identification of most Enterobacter strains needed to be corrected. Fourth, we found that the most common Enterobacter species seen in clinical samples is Enterobacter xiangfangensis rather than Enterobacter cloacae. Fifth, we identified 14 tentative novel Enterobacter and 18 tentative novel non-Enterobacter species. This study highlights that updated and curated taxonomic assignments are the premise of correct species identification. We recommend that future Enterobacter studies need to use the updated taxonomy to avoid misleading information.

The genus Enterobacter comprises common pathogens and has a complicated taxonomy. Precise taxonomic assignation lays a foundation for microbiology. In this study, we updated the Enterobacter taxonomy based on robust genome analyses. We found that all Enterobacter subspecies assignments were incorrect. Enterobacter cloacae subsp. dissolvens and Enterobacter hormaechei subsp. hoffmannii are species (Enterobacter dissolvens and Enterobacter hoffmannii, respectively) rather than subspecies. Enterobacter xiangfangensis, Enterobacter hormaechei subsp. oharae, and Enterobacter hormaechei subsp. steigerwaltii are not Enterobacter hormaechei subspecies but belong to the same species (Enterobacter xiangfangensis). Enterobacter timonensis should be removed to Pseudenterobacter, a novel genus. We then reported two novel species, Enterobacter quasiroggenkampii and Enterobacter quasimori, by genome- and phenotype-based characterization. We also applied the updated taxonomy to curate 1,997 Enterobacter genomes in GenBank. Species identification was changed following our updated taxonomy for the majority of publicly available strains (1,542, 77.2%). The most common Enterobacter species was E. xiangfangensis. We identified 14 novel tentative Enterobacter genomospecies. This study highlights that updated and curated taxonomic assignments are the premise of correct identification.

IMPORTANCEEnterobacter species are major human pathogens. Precise species identification lays a foundation for microbiology, but the taxonomy of Enterobacter is complicated and confusing. In this study, first, we significantly updated the taxonomy of Enterobacter by rigorous genome analyses and found that all subspecies assignments of Enterobacter were incorrect. Second, we characterized and reported two novel Enterobacter species with clinical significance. Third, we curated 1,997 Enterobacter genome sequences deposited in GenBank and found that the species identification of most Enterobacter strains needed to be corrected. Fourth, we found that the most common Enterobacter species seen in clinical samples is Enterobacter xiangfangensis rather than Enterobacter cloacae. Fifth, we identified 14 tentative novel Enterobacter and 18 tentative novel non-Enterobacter species. This study highlights that updated and curated taxonomic assignments are the premise of correct species identification. We recommend that future Enterobacter studies need to use the updated taxonomy to avoid misleading information.

Detection of genome-wide low-frequency mutations with Paired-End and Complementary Consensus Sequencing (PECC-Seq) revealed end-repair-derived artifacts as residual errors

To improve the accuracy and the cost-efficiency of next-generation sequencing in ultralow-frequency mutation detection, we developed the Paired-End and Complementary Consensus Sequencing (PECC-Seq), a PCR-free duplex consensus sequencing approach. PECC-Seq employed shear points as endogenous barcodes to identify consensus sequences from the overlap in the shortened, complementary DNA strand-derived paired-end reads for sequencing error correction. With the high accuracy of PECC-Seq, we identified the characteristic base substitution errors introduced by the end-repair process of mechanical fragmentation-based library preparations, which were prominent at the terminal 7 bp of the library fragments in the 5'-NpCpA-3' and 5'-NpCpT-3' trinucleotide context. As demonstrated at the human genome scale (TK6 cells), after removing these potential end-repair artifacts from the terminal 7 bp, PECC-Seq could reduce the sequencing error frequency to mid-10^-7 with a relatively low sequencing depth. For TA base pairs, the background error rate could be suppressed to mid-10^-8. In mutagen-treated (6 μg/mL methyl methanesulfonate or 12 μg/mL N-nitroso-N-ethylurea) TK6, increases in mutagen treatment-related mutant frequencies could be detected, indicating the potential of PECC-Seq in detecting genome-wide ultra-rare mutations. In addition, our finding on the patterns of end-repair artifacts may provide new insights into further reducing technical errors not only for PECC-Seq, but also for other next-generation sequencing techniques.

Differential Regulation of miRNA Profiles of Human Cells Experimentally Infected by Leishmania donovani Isolated From Indian Visceral Leishmaniasis and Post-Kala-Azar Dermal Leishmaniasis

MicroRNAs are small ribonucleic acid that act as an important regulator of gene expression at the molecular level. However, there is no comparative data on the regulation of microRNAs (miRNAs) in visceral leishmaniasis (VL) and post-kala-azar dermal leishmaniasis (PKDL). In this current study, we compared the expression miRNA profile in host cells (GTHP), with VL strain (GVL) and PKDL strain-infected host cell (GPKDL). Normalized read count comparison between different conditions revealed that the miRNAs are indeed differentially expressed. In GPKDL with respect to GVL and GTHP, a total of 798 and 879 miRNAs were identified, out of which 349 and 518 are known miRNAs, respectively. Comparative analysis of changes in miRNA expression suggested that the involvement of differentially expressed miRNAs in various biological processes like PI3K pathway activation, cell cycle regulation, immunomodulation, apoptosis inhibition, different cytokine production, T-cell phenotypic transitions calcium regulation, and so on. A pathway enrichment study using in silico predicted gene targets of differentially expressed miRNAs showed evidence of potentially universal immune signaling pathway effects. Whereas cytokine-cytokine receptor interaction, phagocytosis, and transforming growth factor beta (TGF-β) signaling pathways were more highly enriched using targets of miRNAs upregulated in GPKDL. These findings could contribute to a better understanding of PKDL pathogenesis. Furthermore, the identified miRNAs could also be used as biomarkers in diagnosis, prognosis, and therapeutics of PKDL infection control.

The Identification of Novel Biomarkers Is Required to Improve Adult SMA Patient Stratification, Diagnosis and Treatment

Spinal muscular atrophy (SMA) is currently classified into five different subtypes, from the most severe (type 0) to the mildest (type 4) depending on age at onset, best motor function achieved, and copy number of the SMN2 gene. The two recent approved treatments for SMA patients revolutionized their life quality and perspectives. However, upon treatment with Nusinersen, the most widely administered therapy up to date, a high degree of variability in therapeutic response was observed in adult SMA patients. These data, together with the lack of natural history information and the wide spectrum of disease phenotypes, suggest that further efforts are needed to develop precision medicine approaches for all SMA patients. Here, we compile the current methods for functional evaluation of adult SMA patients treated with Nusinersen. We also present an overview of the known molecular changes underpinning disease heterogeneity. We finally highlight the need for novel techniques, i.e., -omics approaches, to capture phenotypic differences and to understand the biological signature in order to revise the disease classification and device personalized treatments.

Microbiome Diagnostics

BACKGROUND

During the past decade, breakthroughs in sequencing technology and computational biology have provided the basis for studies of the myriad ways in which microbial communities ("microbiota") in and on the human body influence human health and disease. In almost every medical specialty, there is now a growing interest in accurate and replicable profiling of the microbiota for use in diagnostic and therapeutic application.

CONTENT

This review provides an overview of approaches, challenges, and considerations for diagnostic applications borrowing from other areas of molecular diagnostics, including clinical metagenomics. Methodological considerations and evolving approaches for microbiota profiling from mitochondrially encoded 16S rRNA-based amplicon sequencing to metagenomics and metatranscriptomics are discussed. To improve replicability, at least the most vulnerable steps in testing workflows will need to be standardized and continuous efforts needed to define QC standards. Challenges such as purity of reagents and consumables, improvement of reference databases, and availability of diagnostic-grade data analysis solutions will require joint efforts across disciplines and with manufacturers.

SUMMARY

The body of literature supporting important links between the microbiota at different anatomic sites with human health and disease is expanding rapidly and therapeutic manipulation of the intestinal microbiota is becoming routine. The next decade will likely see implementation of microbiome diagnostics in diagnostic laboratories to fully capitalize on technological and scientific advances and apply them in routine medical practice.

Comparison of Whole Genome (wg-) and Core Genome (cg-) MLST (BioNumericsTM) Versus SNP Variant Calling for Epidemiological Investigation of Pseudomonas aeruginosa

Whole genome sequencing (WGS) is increasingly used for epidemiological investigations of pathogens. While SNP variant calling is currently considered as the most suitable method, the choice of a representative reference genome and the isolate dependency of results limit standardization and affect resolution in an unknown manner. Whole or core genome Multi Locus Sequence Typing (wg-, cg-MLST) represents an attractive alternative. Here, we assess the accuracy of wg- and cg-MLST by comparing results of four Pseudomonas aeruginosa datasets for which epidemiological and genomic data were previously described. Three datasets included 155 isolates from three different sequence types (ST) of P. aeruginosa collected in our ICUs over a 5-year period. The fourth dataset consisted of 10 isolates from an investigation of P. aeruginosa contaminated hand soap. All isolates were previously analyzed by a core SNP approach. In this study, wg- and cg-MLST were performed in BioNumerics^TM using a scheme developed by Applied-Maths. Correlation between SNP calling and wg- or cg-MLST results were evaluated by calculating linear regressions and their coefficient of correlations (R²) between the number of SNPs and the number of allele differences in pairwise comparison of isolates. The number of SNPs and allele difference between isolates with close epidemiological linkage varies between 0–26 and 0–13, respectively. When compared to core-SNP calling, a higher coefficient of correlation was obtained with cgMLST (R² of 0.92–0.99) than with wgMLST (0.78–0.99). In one dataset, a putative homologous recombination of a large DNA fragment (202 loci) was identified among these isolates, affecting its phylogeny, but with no impact on the epidemiological analysis of outbreak isolates. In conclusion, we showed that the P. aeruginosa wgMLST scheme in BioNumerics^TM is as discriminatory as the core-SNP calling approach and apparently useful for outbreak investigations. We also showed that epidemiological linked isolates showed less than 26 SNPs or 13 allele differences. These are important figures for the distinction between outbreak and non-outbreak isolates when interpreting WGS results. However, as P. aeruginosa is highly recombinant, a cgMLST approach is preferable and caution should be addressed to possible recombination of large DNA fragments.

Coding-Complete Genome Sequence of SARS-CoV-2 Isolate from Bangladesh by Sanger Sequencing

A coding-complete genome sequence of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) isolate was revealed. The sample for the virus was isolated from a female patient from Dhaka, Bangladesh, suffering from coronavirus disease-2019 (COVID-19).

A coding-complete genome sequence of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) isolate was revealed. The sample for the virus was isolated from a female patient from Dhaka, Bangladesh, suffering from coronavirus disease-2019 (COVID-19).

Low prevalence of hypervirulent Klebsiella pneumoniae in Anatolia, screened via phenotypic and genotypic testing

Hypervirulent Klebsiella pneumoniae (hvKP) strains are associated with vigorous clinical presentation and relapses. Initially reported from Asia, these variants have spread globally and become an emerging agent of significant health threat. This study was carried out to identify hvKP strains in a previously uninvestigated region and to evaluate the impact of commonly-employed phenotypic and genotypic markers as diagnostic assays. A total of 111 blood culture isolates, collected at a tertiary care center was investigated. The hvKP strains were sought by a string test and the amplification of partial magA, rmpA, iucA and peg344. All products were characterized via sequencing. Evidence for hvKP was observed in 10.8% via iucA amplification (7.2%), string test (2.7%) and magA amplification (0.9%). Specific products were not produced by assays targeting rmpA and peg344 genes. Antibiotic susceptibility patterns compatible with possible extensive or pan-antimicrobial resistance was noted in 66.7% of the hvKP candidate strains. Capsule type in the magA positive strain was characterized as K5. We have detected hvKP in low prevalence at a region with no prior documentation. Targetting the aerobactin gene via iucA amplification provided the most accurate detection in this setting. The epidemiology of hvKP in Anatolia requires elucidation for effective control and management.

Potential role of the skin microbiota in Inflammatory skin diseases

BACKGROUND

Inflammatory skin diseases include a variety of skin diseases, such as seborrheic dermatitis, acne, atopic dermatitis, psoriasis and so on, which are more common and tend to have a significant impact on patients' quality of life. Inflammatory skin diseases often result in physical or psychological distress; however, the pathogenesis of these diseases have not been clearly elucidated. Many factors are involved in the pathogenesis of inflammatory skin diseases, including heredity, environment, immunity, epidermal barrier, mental disorders, infection and so on. In recent years, skin microbiota has been shown to play an important role in inflammatory skin diseases.

AIMS

To elaborate on the specific mechanisms of inflammatory skin diseases induced by microbiota dysbiosis.

METHODS

We introduce the function and influence of skin microbiota in inflammatory skin diseases from the following aspects: Immunity, epigenetics, epidermal barrier and treatment.

RESULTS

Skin microbiota can affect many aspects of the host, such as Immunity, epigenetics, epidermal barrier, and it plays an important role in the pathogenesis of inflammatory skin diseases.

CONCLUSION

Skin microbiota is extremely important for maintaining the health of skin and the dysbiosis of skin microbiota is an important pathogenesis of inflammatory skin diseases.

Next-Generation Sequencing: An Emerging Tool for Drug Designing

BACKGROUND

With the outbreak of high throughput next-generation sequencing (NGS), the biological research of drug discovery has been directed towards the oncology and infectious disease therapeutic areas, with extensive use in biopharmaceutical development and vaccine production.

METHOD

In this review, an effort was made to address the basic background of NGS technologies, potential applications of NGS in drug designing. Our purpose is also to provide a brief introduction of various Nextgeneration sequencing techniques.

DISCUSSIONS

The high-throughput methods execute Large-scale Unbiased Sequencing (LUS) which comprises of Massively Parallel Sequencing (MPS) or NGS technologies. The Next geneinvolved necessarily executes Largescale Unbiased Sequencing (LUS) which comprises of MPS or NGS technologies. These are related terms that describe a DNA sequencing technology which has revolutionized genomic research. Using NGS, an entire human genome can be sequenced within a single day.

CONCLUSION

Analysis of NGS data unravels important clues in the quest for the treatment of various lifethreatening diseases and other related scientific problems related to human welfare.

Recent methods and biosensors for foodborne pathogen detection in fish: progress and future prospects to sustainable aquaculture systems

The aquaculture industry has advanced toward sustainable recirculating systems, in where parameters of food quality are strictly monitored. Despite that, as in the case of conventional aquaculture practices, the recirculating systems also suffer threats from Aeromonas spp., Vibrio spp., Streptococcus spp., among other foodborne pathogens infecting farmed fish. The aquaculture pathogens are routinely detected by conventional PCR methods or antibody-based tests, with the detection protocols confined to laboratory use. Emerging assay technologies and biosensors recently reported in the literature open new opportunities to the development of sensitive, specific, and portable analytical devices to use in the field. Techniques of DNA/RNA analysis, immunoassays and other nanomolecular technologies have been facing important advances in response time, sensitivity, and enhanced power of discrimination among and within species. Moreover, the recent developments of electrochemical and optical signal transduction have facilitated the incorporation of the innovative assays to practical miniaturized devices. In this work, it is provided a critical review over foodborne pathogen detection by existing and promising methods and biosensors applied to fish samples and extended to other food matrices. While isothermal DNA/RNA amplification methods can be highlighted among the assay methods for their promising analytical performance and suitability for point-of-care testing, the electrochemical transduction provides a way to achieve cost-effective biosensors amenable to use in the aquaculture field. The adoption of new methods and biosensors would constitute a step forward in securing sustainable aquaculture systems.

From Nucleotides to Satellite Imagery: Approaches to Identify and Manage the Invasive Pathogen Xylella fastidiosa and Its Insect Vectors in Europe

Biological invasions represent some of the most severe threats to local communities and ecosystems. Among invasive species, the vector-borne pathogen Xylella fastidiosa is responsible for a wide variety of plant diseases and has profound environmental, social and economic impacts. Once restricted to the Americas, it has recently invaded Europe, where multiple dramatic outbreaks have highlighted critical challenges for its management. Here, we review the most recent advances on the identification, distribution and management of X. fastidiosa and its insect vectors in Europe through genetic and spatial ecology methodologies. We underline the most important theoretical and technological gaps that remain to be bridged. Challenges and future research directions are discussed in the light of improving our understanding of this invasive species, its vectors and host–pathogen interactions. We highlight the need of including different, complimentary outlooks in integrated frameworks to substantially improve our knowledge on invasive processes and optimize resources allocation. We provide an overview of genetic, spatial ecology and integrated approaches that will aid successful and sustainable management of one of the most dangerous threats to European agriculture and ecosystems.

Interpreting Mixture Profiles: Comparison between Precision ID GlobalFiler™ NGS STR Panel v2 and Traditional Methods

Forensic investigation for the identification of offenders, recognition of human remains, and verification of family relationships requires the analysis of particular types of highly informative DNA markers, which have high discriminatory power and are efficient for typing degraded samples. These markers, called STRs (Short Tandem Repeats), can be amplified by multiplex-PCR (Polymerase Chain Reaction) allowing attainment of a unique profile through which it is possible to distinguish one individual from another with a high statistical significance. The rapid and progressive evolution of analytical techniques and the advent of Next-Generation Sequencing (NGS) have completely revolutionized the DNA sequencing approach. This technology, widely used today in the diagnostic field, has the advantage of being able to process several samples in parallel, producing a huge volume of data in a short time. At this time, although default parameters of interpretation software are available, there is no general agreement on the interpretation rules of forensic data produced via NGS technology. Here we report a pilot study aimed for a comparison between NGS (Precision ID GlobalFiler™ NGS STR Panel v2, Thermo Fisher Scientific, Waltham, MA, USA) and traditional methods in their ability to identify major and minor contributors in DNA mixtures from saliva and urine samples. A quantity of six mixed samples were prepared for both saliva and urine samples from donors. A total of 12 mixtures were obtained in the ratios of 1:2; 1:4; 1:6; 1:8; 1:10; and 1:20 between minor and major contributors. Although the number of analyzed mixtures is limited, our results confirm that NGS technology offers a huge range of additional information on samples, but cannot ensure a higher sensitivity in respect to traditional methods. Finally, the Precision ID GlobalFiler™ NGS STR Panel v2 is a powerful method for kinship analyses and typing reference samples, but its use in biological evidence should be carefully considered on the basis of the characteristics of the evidence.

Novel strategies for rapid identification and susceptibility testing of MRSA

INTRODUCTION

Methicillin-resistant Staphylococcus aureus (MRSA) is associated with adverse clinical outcomes and increased morbidity, mortality, length of hospital stay, and health-care costs. Rapid diagnosis of MRSA infections has been associated with positive impact on clinical outcomes.

AREAS COVERED

We searched relevant papers in PubMed for the last 10 years. In major papers, we scanned the bibliographies to ensure that important articles were included. This review describes screening and diagnostic test methods for MRSA and their analytical performances with a focus on rapid molecular-based assays including those that are on the horizon. Future novel technologies will allow more rapid detection of phenotypic resistance. In the case of whole-genome sequencing, detection of mutations may predict resistance, transmission, and virulence.

EXPERT OPINION

Currently there are many diagnostic options for the detection of MRSA in surveillance and clinical samples. In general, these are highly accurate and have resulted in improvements in targeted management and reduction in hospital or intensive care unit length of stay for both MSSA and MRSA. Impact on mortality has been variable. Promising novel technologies will not only accurately identify pathogens and detect their resistance markers but will allow discovery of virulence determinants that might further affect patient management.

SERS-Based Biosensors for Virus Determination with Oligonucleotides as Recognition Elements

Viral infections are among the main causes of morbidity and mortality of humans; sensitive and specific diagnostic methods for the rapid identification of viral pathogens are required. Surface-enhanced Raman spectroscopy (SERS) is one of the most promising techniques for routine analysis due to its excellent sensitivity, simple and low-cost instrumentation and minimal required sample preparation. The outstanding sensitivity of SERS is achieved due to tiny nanostructures which must be assembled before or during the analysis. As for specificity, it may be provided using recognition elements. Antibodies, complimentary nucleic acids and aptamers are the most usable recognition elements for virus identification. Here, SERS-based biosensors for virus identification with oligonucleotides as recognition elements are reviewed, and the potential of these biosensors is discussed.

Cultivation-Free Typing of Bacteria Using Optical DNA Mapping

A variety of pathogenic bacteria can infect humans, and rapid species identification is crucial for the correct treatment. However, the identification process can often be time-consuming and depend on the cultivation of the bacterial pathogen(s). Here, we present a stand-alone, enzyme-free, optical DNA mapping assay capable of species identification by matching the intensity profiles of large DNA molecules to a database of fully assembled bacterial genomes (>10 000). The assay includes a new data analysis strategy as well as a general DNA extraction protocol for both Gram-negative and Gram-positive bacteria. We demonstrate that the assay is capable of identifying bacteria directly from uncultured clinical urine samples, as well as in mixtures, with the potential to be discriminative even at the subspecies level. We foresee that the assay has applications both within research laboratories and in clinical settings, where the time-consuming step of cultivation can be minimized or even completely avoided.

Concordance between epidemiological evaluation of probability of transmission and whole genome sequence relatedness among hospitalized patients acquiring Klebsiella pneumoniae carbapenemase-producing Klebsiella pneumoniae

OBJECTIVES

We aimed to evaluate the concordance between epidemiologically determined transmission and genetic linkage of Klebsiella pneumoniae carbapenemase (KPC)-producing Klebsiella pneumoniae (KPC-Kp).

METHODS

We included consecutive KPC-Kp carriers between December 2016 and April 2017 in a hospital endemic for KPC-Kp. We assessed epidemiological relatedness between patients by prospective investigations by the infection control team. The probability of epidemiological relatedness was classified into four groups: no suspected transmission, low, moderate and high probability of transmission. Whole-genome sequencing of isolates was performed. Genetic linkage between KPC-Kp isolates was expressed by distance between isolates in single nucleotide polymorphisms (SNPs). We established an SNP cut-off defining a different strain based on the reconstructed phylogenetic tree. We compared the epidemiological and genetic linkage of all isolates from all patients.

RESULTS

The study included 25 KPC-Kp carriers with 49 isolates. SNP variance was available for 1129 crossed patient-isolate pairs. Genomic linkage, based on a cut-off of 80 SNPs to define related isolates, was found in 115/708 (16.2%) of isolates with no transmission suspected epidemiologically, 27/319 (8.5%) of low, 11/26 (42.3%) of moderate and 64/76 (84.2%) of high epidemiological transmission risk determination (p < 0.001 for trend). Similar results and significant trends were shown on sensitivity analyses using a lower SNP cut-off (six SNPs) and patient-isolate unique pairs, analysing the first isolate from each patient.

CONCLUSIONS

While significant concordance between epidemiological and genomic transmission patterns was found, epidemiological investigations of transmission are limited by the possibility of unidentified transmissions or over-estimation of associations. Genetic linkage analysis is an important aid to epidemiological transmission assessment.

The effects of CS@Fe3O4 nanoparticles combined with microwave or far infrared thawing on microbial diversity of red seabream (Pagrus major) fillets based on high-throughput sequencing

The present study investigated the effects of CS@Fe₃O₄ nanoparticles combined with microwave or far infrared thawing on microbial diversity of red seabream (Pagrus major) fillets in terms of thawing loss, pH, TVB-N, classical microbiological enumeration and high-throughput sequencing, and the same parameters were also studied for 24 h after thawing. Four thawing methods were used: microwave thawing (MT), far-infrared thawing (FT), CS@Fe₃O₄ nanoparticles combined with microwave thawing (CMT) and CS@Fe₃O₄ nanoparticles combined with far-infrared thawing (CFT). The results showed that CFT and CMT had lower values of pH and TVB-N compared to the FT and MT. Based on conventional microbial count analysis, CFT and CMT samples also maintained lower TVC, pseudomonas and LAB counts. Using high-throughput sequencing analysis, Compared with FT and MT, CFT and CMT samples showed a significant decrease in the proportion of the Pseudomonadaceae flora. However, the proportion of Pseudomonas, Bacillaceae and Thermaceae also increased significantly after 24 h of storage, which indicated that become the predominant microbiota in red seabream (Pagrus major) fillets.

Emerging strategies for the development of food industries

Undoubtedly, the food industry is undergoing a dynamic process of transformation in its continual development in order to meet the requirements and solve the great problems represented by a constantly growing global population and food claimant in both quantity and quality. In this sense, it is necessary to evaluate the technological trends and advances that will change the landscape of the food processing industry, highlighting the latest requirements for equipment functionality. In particular, it is crucial to evaluate the influence of sustainable green biotechnology-based technologies to consolidate the food industry of the future, today, and it must be done by analyzing the mega-consumption trends that shape the future of industry, which range from local sourcing to on-the-go food, to an increase in organic foods and clean labels (understanding ingredients on food labels). While these things may seem alien to food manufacturing, they have a considerable influence on the way products are manufactured. This paper reviews in detail the conditions of the food industry, and particularly analyzes the application of emerging technologies in food preservation, extraction of bioactive compounds, bioengineering tools and other bio-based strategies for the development of the food industry.