Bacterial genome sequencing in the clinic: bioinformatic challenges and solutions

Diagnosis of bacteria from the CMNR group in farm animals

The CMNR group comprises bacteria of the genera Corynebacterium, Mycobacterium, Nocardia, and Rhodococcus and share cell wall and DNA content characteristics. Many pathogenic CMNR bacteria cause diseases such as mastitis, lymphadenitis, and pneumonia in farmed animals, which cause economic losses for breeders and represent a threat to public health. Traditional diagnosis in CMNR involves isolating target bacteria on general or selective media and conducting metabolic analyses with the assistance of laboratory biochemical identification systems. Advanced mass spectrometry may also support diagnosing these bacteria in the clinic's daily routine despite some challenges, such as the need for isolated bacteria. In difficult identification among some CMNR members, molecular methods using polymerase chain reaction (PCR) emerge as reliable options for correct specification that is sometimes achieved directly from clinical samples such as tracheobronchial aspirates and feces. On the other hand, immunological diagnostics such as the skin test or Enzyme-Linked Immunosorbent Assay (ELISA) for Mycobacterium tuberculosis yield promising results in subclinical infections with no bacterial growth involved. In this review, we present the methods most commonly used to diagnose pathogenic CMNR bacteria and discuss their advantages and limitations, as well as challenges and perspectives on adopting new technologies in diagnostics.

Innovative Biomedical and Technological Strategies for the Control of Bacterial Growth and Infections

Antibiotics comprise one of the most successful groups of pharmaceutical products. Still, they have been associated with developing bacterial resistance, which has become one of the most severe problems threatening human health today. This context has prompted the development of new antibiotics or co-treatments using innovative tools to reverse the resistance context, combat infections, and offer promising antibacterial therapy. For the development of new alternatives, strategies, and/or antibiotics for controlling bacterial growth, it is necessary to know the target bacteria, their classification, morphological characteristics, the antibiotics currently used for therapies, and their respective mechanisms of action. In this regard, genomics, through the sequencing of bacterial genomes, has generated information on diverse genetic resources, aiding in the discovery of new molecules or antibiotic compounds. Nanotechnology has been applied to propose new antimicrobials, revitalize existing drug options, and use strategic encapsulating agents with their biochemical characteristics, making them more effective against various bacteria. Advanced knowledge in bacterial sequencing contributes to the construction of databases, resulting in advances in bioinformatics and the development of new antimicrobials. Moreover, it enables in silico antimicrobial susceptibility testing without the need to cultivate the pathogen, reducing costs and time. This review presents new antibiotics and biomedical and technological innovations studied in recent years to develop or improve natural or synthetic antimicrobial agents to reduce bacterial growth, promote well-being, and benefit users.

Results of the 2020 Genomic Proficiency Test for the network of European Union Reference Laboratory for Antimicrobial Resistance assessing whole-genome-sequencing capacities

The global surveillance and outbreak investigation of antimicrobial resistance (AMR) is amidst a paradigm shift from traditional biology to bioinformatics. This is due to developments in whole-genome-sequencing (WGS) technologies, bioinformatics tools, and reduced costs. The increased use of WGS is accompanied by challenges such as standardization, quality control (QC), and data sharing. Thus, there is global need for inter-laboratory WGS proficiency test (PT) schemes to evaluate laboratories' capacity to produce reliable genomic data. Here, we present the results of the first iteration of the Genomic PT (GPT) organized by the Global Capacity Building Group at the Technical University of Denmark in 2020. Participating laboratories sequenced two isolates and corresponding DNA of Salmonella enterica, Escherichia coli and Campylobacter coli, using WGS methodologies routinely employed at their laboratories. The participants' ability to obtain consistently good-quality WGS data was assessed based on several QC WGS metrics. A total of 21 laboratories from 21 European countries submitted WGS and meta-data. Most delivered high-quality sequence data with only two laboratories identified as overall underperforming. The QC metrics, N50 and number of contigs, were identified as good indicators for high-sequencing quality. We propose QC thresholds for N50 greater than 20 000 and 25 000 for Campylobacter coli and Escherichia coli, respectively, and number of contigs >200 bp greater than 225, 265 and 100 for Salmonella enterica, Escherichia coli and Campylobacter coli, respectively. The GPT2020 results confirm the importance of systematic QC procedures, ensuring the submission of reliable WGS data for surveillance and outbreak investigation to meet the requirements of the paradigm shift in methodology.

Genome-Wide Pathway Exploration of the Epidermidibacterium keratini EPI-7T

Functional cosmetics industries using skin microbiome screening and beneficial materials isolated from key microorganisms are receiving increasing attention. Since Epidermidibacterium keratini EPI-7T was first discovered in human skin, previous studies have confirmed that it can produce a new pyrimidine compound, 1,1'-biuracil, having anti-aging effects on human skin. Therefore, we conducted genomic analyses to judge the use value of E. keratini EPI-7T and provide up-to-date information. Whole-genome sequencing analysis of E. keratini EPI-7T was performed to generate new complete genome and annotation information. E. keratini EPI-7T genome was subjected to comparative genomic analysis with a group of closely-related strains and skin flora strains through bioinformatic analysis. Furthermore, based on annotation information, we explored metabolic pathways for valuable substances that can be used in functional cosmetics. In this study, the whole-genome sequencing (WGS) and annotation results of E. keratini EPI-7T were improved, and through comparative analysis, it was confirmed that the E. keratini EPI-7T has more metabolite-related genes than comparison strains. In addition, we annotated the vital genes for biosynthesis of 20 amino acids, orotic acid, riboflavin (B2) and chorismate. In particular, we were able to prospect that orotic acid could accumulate inside E. keratini EPI-7T under uracil-enriched conditions. Therefore, through a genomics approach, this study aims to provide genetic information for the hidden potential of E. keratini EPI-7T and the strain development and biotechnology utilization to be conducted in further studies.

GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking): A methodology to rapidly leverage whole genome sequencing of bacterial isolates for clinical identification

Whole genome sequencing (WGS) of clinical bacterial isolates has the potential to transform the fields of diagnostics and public health. To realize this potential, bioinformatic software that reports identification results needs to be developed that meets the quality standards of a diagnostic test. We developed GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking) using k-mer based strategies for identification of bacteria based on WGS reads. GAMBIT incorporates this algorithm with a highly curated searchable database of 48,224 genomes. Herein, we describe validation of the scoring methodology, parameter robustness, establishment of confidence thresholds and the curation of the reference database. We assessed GAMBIT by way of validation studies when it was deployed as a laboratory-developed test in two public health laboratories. This method greatly reduces or eliminates false identifications which are often detrimental in a clinical setting.

One Day in Denmark: Comparison of Phenotypic and Genotypic Antimicrobial Susceptibility Testing in Bacterial Isolates From Clinical Settings

Antimicrobial susceptibility testing (AST) should be fast and accurate, leading to proper interventions and therapeutic success. Clinical microbiology laboratories rely on phenotypic methods, but the continuous improvement and decrease in the cost of whole-genome sequencing (WGS) technologies make them an attractive alternative. Studies evaluating the performance of WGS-based prediction of antimicrobial resistance (AMR) for selected bacterial species have shown promising results. There are, however, significant gaps in the literature evaluating the applicability of WGS as a diagnostics method in real-life clinical settings against the range of bacterial pathogens experienced there. Thus, we compared standard phenotypic AST results with WGS-based predictions of AMR profiles in bacterial isolates without preselection of defined species, to evaluate the applicability of WGS as a diagnostics method in clinical settings. We collected all bacterial isolates processed by all Danish Clinical Microbiology Laboratories in 1 day. We randomly selected 500 isolates without any preselection of species. We performed AST through standard broth microdilution (BMD) for 488 isolates (n = 6,487 phenotypic AST results) and compared results with in silico antibiograms obtained through WGS (Illumina NextSeq) followed by bioinformatics analyses using ResFinder 4.0 (n = 5,229 comparisons). A higher proportion of AMR was observed for Gram-negative bacteria (10.9%) than for Gram-positive bacteria (6.1%). Comparison of BMD with WGS data yielded a concordance of 91.7%, with discordant results mainly due to phenotypically susceptible isolates harboring genetic AMR determinants. These cases correspond to 6.2% of all isolate-antimicrobial combinations analyzed and to 6.8% of all phenotypically susceptible combinations. We detected fewer cases of phenotypically resistant isolates without any known genetic resistance mechanism, particularly 2.1% of all combinations analyzed, which corresponded to 26.4% of all detected phenotypic resistances. Most discordances were observed for specific combinations of species-antimicrobial: macrolides and tetracycline in streptococci, ciprofloxacin and β-lactams in combination with β-lactamase inhibitors in Enterobacterales, and most antimicrobials in Pseudomonas aeruginosa. WGS has the potential to be used for surveillance and routine clinical microbiology. However, in clinical microbiology settings and especially for certain species and antimicrobial agent combinations, further developments in AMR gene databases are needed to ensure higher concordance between in silico predictions and expected phenotypic AMR profiles.

Comparing Core-genome MLST with PFGE and MLST for cluster analysis of Carbapenem-resistant Acinetobacter baumannii

OBJECTIVES

Carbapenem-resistant Acinetobacter baumannii (CRAB) is a prevalent pathogen contributing to hospital infections. Pulsed-field gel electrophoresis, multilocus sequence typing and core-genome MLST are frequently used methods to illuminate the nosocomial transmission of CRAB. In this study, we compared the discriminatory power of the three typing methods.

METHODS

Antimicrobial susceptibility tests were performed by the broth microdilution and Vitek2 methods. PFGE, MLST and cgMLST were conducted to determine the clonality and phylogenetic relationship of the strains. Whole-genome sequence data were acquired by an Illumina HiSeq 2000, and cgMLST was analysed by the Ridom SeqSphere+ v7.2.3 software.

RESULTS

A total of 149 carbapenem-resistant A. baumannii isolates had 15 different PFGE profiles (A-O type), and 73 of the isolates had related subtypes (A1 and A2) accounting for the majority of type A isolates. The maximum-likelihood phylogenetic analysis based on the cgMLST genes grouped the same PFGE clonal pattern A into 9 different clusters. ST_Pasteur grouped all the strains into ST2, whereas ST_Oxford grouped the PFGE clonal pattern A isolates into 6 STs. In addition, the gdhB allele in the ST_Oxford scheme had two copies in 5 strains, which complicated the ST_Oxford typing.

CONCLUSIONS

In conclusion, cgMLST was more discriminant than PFGE and MLST. CgMLST is the most suitable and comprehensive method for genotyping A. baumannii in surveillance and epidemiological research.

Genome wide association study of Escherichia coli bloodstream infection isolates identifies genetic determinants for the portal of entry but not fatal outcome

Escherichia coli is an important cause of bloodstream infections (BSI), which is of concern given its high mortality and increasing worldwide prevalence. Finding bacterial genetic variants that might contribute to patient death is of interest to better understand infection progression and implement diagnostic methods that specifically look for those factors. E. coli samples isolated from patients with BSI are an ideal dataset to systematically search for those variants, as long as the influence of host factors such as comorbidities are taken into account. Here we performed a genome-wide association study (GWAS) using data from 912 patients with E. coli BSI from hospitals in Paris, France. We looked for associations between bacterial genetic variants and three patient outcomes (death at 28 days, septic shock and admission to intensive care unit), as well as two portals of entry (urinary and digestive tract), using various clinical variables from each patient to account for host factors. We did not find any association between genetic variants and patient outcomes, potentially confirming the strong influence of host factors in influencing the course of BSI; we however found a strong association between the papGII operon and entrance of E. coli through the urinary tract, which demonstrates the power of bacterial GWAS when applied to actual clinical data. Despite the lack of associations between E. coli genetic variants and patient outcomes, we estimate that increasing the sample size by one order of magnitude could lead to the discovery of some putative causal variants. Given the wide adoption of bacterial genome sequencing of clinical isolates, such sample sizes may be soon available.

Metagenomics studies for the diagnosis and treatment of prostate cancer

AIM

Mutation occurs in the prostate cell genes, leading to abnormal prostate proliferation and ultimately cancer. Prostate cancer (PC) is one of the most common cancers amongst men, and its prevalence worldwide increases relative to men's age. About 16% of the world's cancers are the result of microbes in the human body. Impaired population balance of symbiosis microbes in the human reproductive system is linked to PC development.

DISCUSSION

With the advent of metagenomics science, the genome sequence of the microbiota of the human body has been unveiled. Therefore, it is now possible to identify a higher range of microbiome changes in PC tissue via the Next Generation Technique, which will have positive consequences in personalized medicine. In this review, we intend to question the role of metagenomics studies in the diagnosis and treatment of PC.

CONCLUSION

The microbial imbalance in the men's genital tract might have an effect on prostate health. Based on next-generation sequencing-generated data, Proteobacteria, Firmicutes, Actinobacteria, and Bacteriodetes are the nine frequent phyla detected in a PC sample, which might be involved in inducing mutation in the prostate cells that cause cancer.

Clinical and Microbiological Characteristics of Recurrent Escherichia coli Bacteremia

The causative agents of recurrent Escherichia coli bacteremia can be genetically identical or discordant, but the differences between them remain unclear. This study aimed to explore these differences, with regard to their clinical and microbiological features. Patients were recruited from a Japanese tertiary teaching hospital based on blood culture data and the incidence of recurrent E. coli bacteremia. We compared the patients' clinical and microbiological characteristics between the two groups (those with identical or discordant E. coli bacteremia) divided by the result of enterobacterial repetitive intergenic consensus PCR. Among 70 pairs of recurrent E. coli bacteremia strains, 49 pairs (70%) were genetically identical. Patients with genetically identical or discordant E. coli bacteremia were more likely to have renal failure or neoplasms, respectively. The virulence factor (VF) scores of genetically identical E. coli strains were significantly higher than those of genetically discordant strains, with the prevalence of eight VF genes being significantly higher in genetically identical E. coli strains. No significant differences were found between the two groups regarding antimicrobial susceptibility and biofilm formation potential. This study showed that genetically identical E. coli bacteremia strains have more VF genes than genetically discordant strains in recurrent E. coli bacteremia.

IMPORTANCEEscherichia coli causes bloodstream infection, although not all strains are pathogenic to humans. In some cases, this infection reoccurs, and several reports have described the clinical characteristics and/or molecular microbiology of recurrent Escherichia coli bacteremia. However, these studies focused on patients with specific characteristics, and they included cases caused by microorganisms other than Escherichia coli. Hence, little is known about the pathogenicity of Escherichia coli isolated from the recurrent one. The significance of our study is in evaluating the largest cohorts to date, as no cohort studies have been conducted on this topic.

Overcoming Data Bottlenecks in Genomic Pathogen Surveillance

Performing whole genome sequencing (WGS) for the surveillance of antimicrobial resistance offers the ability to determine not only the antimicrobials to which rates of resistance are increasing, but also the evolutionary mechanisms and transmission routes responsible for the increase at local, national, and global scales. To derive WGS-based outputs, a series of processes are required, beginning with sample and metadata collection, followed by nucleic acid extraction, library preparation, sequencing, and analysis. Throughout this pathway there are many data-related operations required (informatics) combined with more biologically focused procedures (bioinformatics). For a laboratory aiming to implement pathogen genomics, the informatics and bioinformatics activities can be a barrier to starting on the journey; for a laboratory that has already started, these activities may become overwhelming. Here we describe these data bottlenecks and how they have been addressed in laboratories in India, Colombia, Nigeria, and the Philippines, as part of the National Institute for Health Research Global Health Research Unit on Genomic Surveillance of Antimicrobial Resistance. The approaches taken include the use of reproducible data parsing pipelines and genome sequence analysis workflows, using technologies such as Data-flo, the Nextflow workflow manager, and containerization of software dependencies. By overcoming barriers to WGS implementation in countries where genome sampling for some species may be underrepresented, a body of evidence can be built to determine the concordance of antimicrobial sensitivity testing and genome-derived resistance, and novel high-risk clones and unknown mechanisms of resistance can be discovered.

Amplification of Femtograms of Bacterial DNA Within 3 h Using a Digital Microfluidics Platform for MinION Sequencing

Whole genome sequencing is emerging as a promising tool for the untargeted detection of a broad range of microbial species for diagnosis and analysis. However, it is logistically challenging to perform the multistep process from sample preparation to DNA amplification to sequencing and analysis within a short turnaround time. To address this challenge, we developed a digital microfluidic device for rapid whole genome amplification of low-abundance bacterial DNA and compared results with conventional in-tube DNA amplification. In this work, we chose Corynebacterium glutamicum DNA as a bacterial target for method development and optimization, as it is not a common contaminant. Sequencing was performed in a hand-held Oxford Nanopore Technologies MinION sequencer. Our results show that using an in-tube amplification approach, at least 1 pg starting DNA is needed to reach the amount required for successful sequencing within 2 h. While using a digital microfluidic device, it is possible to amplify as low as 10 fg of C. glutamicum DNA (equivalent to the amount of DNA within a single bacterial cell) within 2 h and to identify the target bacterium within 30 min of MinION sequencing-100× lower than the detection limit of an in-tube amplification approach. We demonstrate the detection of C. glutamicum DNA in a mock community DNA sample and characterize the limit of bacterial detection in the presence of human cells. This approach can be used to identify microbes with minute amounts of genetic material in samples depleted of human cells within 3 h.

Validation, Implementation, and Clinical Utility of Whole Genome Sequence-Based Bacterial Identification in the Clinical Microbiology Laboratory

The application of next-generation sequencing extends from microbial identification to epidemiologic insight and antimicrobial resistance prediction. Despite this potential, the roadblock for clinical laboratories lies in implementation and validation of such complex technology and data analysis. Here, we describe a validation study using whole-genome sequencing (WGS) for pan-bacterial identification (ID) in a clinical laboratory setting, and discuss the clinical relevance. A diverse set of 125 bacterial isolates, including a subset of isolates without genus (25) and/or species (10) ID, were analyzed by de novo assembly and reference genome mapping. The 16S rRNA, rpoB, and groEL genes were used for ID. Using WGS, 100% (89 of 89) and 89% (79 of 89) of isolates were identified to the genus and species levels, respectively. WGS also provided improved results for the majority of isolates (25 of 35) that were reported originally with genus-only or descriptive IDs. Chart review identified cases in which improved genus and/or species level ID by WGS may have had a positive impact on patient care. Reasons included the use of an ineffective antibiotic owing to unclear ID, use of antibiotics when not clinically indicated, and help with an outbreak investigation. The implementation of next-generation sequencing in a clinical microbiology setting is a challenging but necessary task. Our study provides a model for the validation and implementation of bacterial ID by WGS in such a setting.

Genomic Characterization of Fluoroquinolone-Resistant Thermophilic Campylobacter Strains Isolated from Layer Chicken Feces in Gangneung, South Korea by Whole-Genome Sequencing

Thermophilic Campylobacter species of poultry origin have been associated with up to 80% of human campylobacteriosis cases. Layer chickens have received less attention as possible reservoirs of Campylobacter species. Initially, the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of two archived Campylobacter isolates (Campylobacter jejuni strain 200605 and Campylobacter coli strain 200606) from layer chickens to five antimicrobials (ciprofloxacin, nalidixic acid, erythromycin, tetracycline, and gentamicin) were determined using broth microdilution while the presence of selected antimicrobial resistance genes was performed by polymerase chain reaction (PCR) using specific primers. Whole-genome sequencing (WGS) was performed by the Illumina HiSeq X platform. The analysis involved antimicrobial resistance genes, virulome, multilocus sequence typing (MLST), and phylogeny. Both isolates were phenotypically resistant to ciprofloxacin (MIC: 32 vs. 32 µg/mL), nalidixic acid (MIC: 128 vs. 64 µg/mL), and tetracycline (MIC: 64 vs. 64 µg/mL), but sensitive to erythromycin (MIC: 1 vs. 2 µg/mL) and gentamicin (MIC: 0.25 vs. 1 µg/mL) for C. jejuni strain 200605 and C. coli strain 200606, respectively. WGS confirmed C257T mutation in the gyrA gene and the presence of cmeABC complex conferring resistance to FQs in both strains. Both strains also exhibited tet(O) genes associated with tetracycline resistance. Various virulence genes associated with motility, chemotaxis, and capsule formation were found in both isolates. However, the analysis of virulence genes showed that C. jejuni strain 200605 is more virulent than C. coli strain 200606. The MLST showed that C. jejuni strain 200605 belongs to sequence type ST-5229 while C. coli strain 200606 belongs to ST-5935, and both STs are less common. The phylogenetic analysis clustered C. jejuni strain 200605 along with other strains reported in Korea (CP028933 from chicken and CP014344 from human) while C. coli strain 200606 formed a separate cluster with C. coli (CP007181) from turkey. The WGS confirmed FQ-resistance in both strains and showed potential virulence of both strains. Further studies are recommended to understand the reasons behind the regional distribution (Korea, China, and Vietnam) of such rare STs.

Beating the Bio-Terror Threat with Rapid Antimicrobial Susceptibility Testing

A bioterror event using an infectious bacterium may lead to catastrophic outcomes involving morbidity and mortality as well as social and psychological stress. Moreover, a bioterror event using an antibiotic resistance engineered bacterial agent may raise additional concerns. Thus, preparedness is essential to preclude and control the dissemination of the bacterial agent as well as to appropriately and promptly treat potentially exposed individuals or patients. Rates of morbidity, death, and social anxiety can be drastically reduced if the rapid delivery of antimicrobial agents for post-exposure prophylaxis and treatment is initiated as soon as possible. Availability of rapid antibiotic susceptibility tests that may provide key recommendations to targeted antibiotic treatment is mandatory, yet, such tests are only at the development stage. In this review, we describe the recently published rapid antibiotic susceptibility tests implemented on bioterror bacterial agents and discuss their assimilation in clinical and environmental samples.

Comparison of traditional methods and high-throughput genetic sequencing in the detection of pathogens in pulmonary infectious diseases

Background

The major causes of pulmonary infections are various microorganisms. This study aimed to compare the positive rates of pathogenic microorganism DNA/RNA high-throughput genetic sequencing (PMseq), which is an emerging technique, with traditional methods for pulmonary disease detection, and to investigate the differences in different sample types.

Methods

Bronchoalveolar lavage fluid (BALF) and venous blood samples from 104 patients were collected for detection.

Results

The positive rates of PMseq in BALF and venous blood were both significantly higher than those of traditional methods in the same sample (P<0.001). For BALF, the detection sensitivities were 96.9% for non-febrile patients and 100% for febrile patients. For venous blood, the detection sensitivities were 50.0% for non-febrile patients and 81.3% for febrile patients. There was no statistical difference in the sensitivity of venous blood samples with or without fever (P=0.075). For patients without fever, the sensitivity of BALF was much higher than venous blood samples (P<0.001). In patients with fever, there were no significant differences between different samples.

Conclusions

This study showed that PMseq has a higher positive rate for the detection of pulmonary diseases. For patients without fever, it is recommended to use BALF instead of venous blood samples because of the higher sensitivity. However, for patients with fever, venous blood samples can be used when bronchoalveolar lavage is inconvenient.

Whole-Genome Sequencing for Investigating a Health Care-Associated Outbreak of Carbapenem-Resistant Acinetobacter baumannii

Carbapenem-resistant Acinetobacter baumannii (CRAB) outbreaks in hospital settings challenge the treatment of patients and infection control. Understanding the relatedness of clinical isolates is important in distinguishing outbreak isolates from sporadic cases. This study investigated 11 CRAB isolates from a hospital outbreak by whole-genome sequencing (WGS), utilizing various bioinformatics tools for outbreak analysis. The results of multilocus sequence typing (MLST), single nucleotide polymorphism (SNP) analysis, and phylogenetic tree analysis by WGS through web-based tools were compared, and repetitive element polymerase chain reaction (rep-PCR) typing was performed. Through the WGS of 11 A. baumannii isolates, three clonal lineages were identified from the outbreak. The coexistence of bla_OXA-23, bla_OXA-66, bla_ADC-25, and armA with additional aminoglycoside-inactivating enzymes, predicted to confer multidrug resistance, was identified in all isolates. The MLST Oxford scheme identified three types (ST191, ST369, and ST451), and, through whole-genome MLST and whole-genome SNP analyses, different clones were found to exist within the MLST types. wgSNP showed the highest discriminatory power with the lowest similarities among the isolates. Using the various bioinformatics tools for WGS, CRAB outbreak analysis was applicable and identified three discrete clusters differentiating the separate epidemiologic relationships among the isolates.

Current challenges and best-practice protocols for microbiome analysis

Analyzing the microbiome of diverse species and environments using next-generation sequencing techniques has significantly enhanced our understanding on metabolic, physiological and ecological roles of environmental microorganisms. However, the analysis of the microbiome is affected by experimental conditions (e.g. sequencing errors and genomic repeats) and computationally intensive and cumbersome downstream analysis (e.g. quality control, assembly, binning and statistical analyses). Moreover, the introduction of new sequencing technologies and protocols led to a flood of new methodologies, which also have an immediate effect on the results of the analyses. The aim of this work is to review the most important workflows for 16S rRNA sequencing and shotgun and long-read metagenomics, as well as to provide best-practice protocols on experimental design, sample processing, sequencing, assembly, binning, annotation and visualization. To simplify and standardize the computational analysis, we provide a set of best-practice workflows for 16S rRNA and metagenomic sequencing data (available at https://github.com/grimmlab/MicrobiomeBestPracticeReview).

Artificial intelligence and synthetic biology approaches for human gut microbiome

The gut microbiome comprises a variety of microorganisms whose genes encode proteins to carry out crucial metabolic functions that are responsible for the majority of health-related issues in human beings. The advent of the technological revolution in artificial intelligence (AI) assisted synthetic biology (SB) approaches will play a vital role in the modulating the therapeutic and nutritive potential of probiotics. This can turn human gut as a reservoir of beneficial bacterial colonies having an immense role in immunity, digestion, brain function, and other health benefits. Hence, in the present review, we have discussed the role of several gene editing tools and approaches in synthetic biology that have equipped us with novel tools like Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR-Cas) systems to precisely engineer probiotics for diagnostic, therapeutic and nutritive value. A brief discussion over the AI techniques to understand the metagenomic data from the healthy and diseased gut microbiome is also presented. Further, the role of AI in potentially impacting the pace of developments in SB and its current challenges is also discussed. The review also describes the health benefits conferred by engineered microbes through the production of biochemicals, nutraceuticals, drugs or biotherapeutics molecules etc. Finally, the review concludes with the challenges and regulatory concerns in adopting synthetic biology engineered microbes for clinical applications. Thus, the review presents a synergistic approach of AI and SB toward human gut microbiome for better health which will provide interesting clues to researchers working in the area of rapidly evolving food and nutrition science.

Whole-Genome Sequencing and Bioinformatic Analysis of Environmental, Agricultural, and Human Campylobacter jejuni Isolates From East Tennessee

As a leading cause of bacterial-derived gastroenteritis worldwide, Campylobacter jejuni has a significant impact on human health in both the developed and developing worlds. Despite its prevalence as a human pathogen, the source of these infections remains poorly understood due to the mutation frequency of the organism and past limitations of whole genome analysis. Recent advances in both whole genome sequencing and computational methods have allowed for the high-resolution analysis of intraspecies diversity, leading multiple groups to postulate that these approaches may be used to identify the sources of Campylobacter jejuni infection. To address this hypothesis, our group conducted a regionally and temporally restricted sampling of agricultural and environmental Campylobacter sources and compared isolated C. jejuni genomes to those that caused human infections in the same region during the same time period. Through a network analysis comparing genomes from various sources, we found that human C. jejuni isolates clustered with those isolated from cattle and chickens, indicating these as potential sources of human infection in the region.

Major role of iron uptake systems in the intrinsic extra-intestinal virulence of the genus Escherichia revealed by a genome-wide association study

The genus Escherichia is composed of several species and cryptic clades, including E. coli, which behaves as a vertebrate gut commensal, but also as an opportunistic pathogen involved in both diarrheic and extra-intestinal diseases. To characterize the genetic determinants of extra-intestinal virulence within the genus, we carried out an unbiased genome-wide association study (GWAS) on 370 commensal, pathogenic and environmental strains representative of the Escherichia genus phylogenetic diversity and including E. albertii (n = 7), E. fergusonii (n = 5), Escherichia clades (n = 32) and E. coli (n = 326), tested in a mouse model of sepsis. We found that the presence of the high-pathogenicity island (HPI), a ~35 kbp gene island encoding the yersiniabactin siderophore, is highly associated with death in mice, surpassing other associated genetic factors also related to iron uptake, such as the aerobactin and the sitABCD operons. We confirmed the association in vivo by deleting key genes of the HPI in E. coli strains in two phylogenetic backgrounds. We then searched for correlations between virulence, iron capture systems and in vitro growth in a subset of E. coli strains (N = 186) previously phenotyped across growth conditions, including antibiotics and other chemical and physical stressors. We found that virulence and iron capture systems are positively correlated with growth in the presence of numerous antibiotics, probably due to co-selection of virulence and resistance. We also found negative correlations between virulence, iron uptake systems and growth in the presence of specific antibiotics (i.e. cefsulodin and tobramycin), which hints at potential “collateral sensitivities” associated with intrinsic virulence. This study points to the major role of iron capture systems in the extra-intestinal virulence of the genus Escherichia.

Bacterial isolates belonging to the genus Escherichia can be human commensals but also opportunistic pathogens, with the ability to cause extra-intestinal infection. There is therefore the need to identify the genetic elements that favour extra-intestinal virulence, so that virulent bacterial isolates can be identified through genome analysis and potential treatment strategies be developed. To reduce the influence of host variability on virulence, we have used a mouse model of sepsis to characterize the virulence of 370 strains belonging to the genus Escherichia, for which whole genome sequences were also available. We have used a statistical approach called Genome-Wide Association Study (GWAS) to show how the presence of genes that encode for iron scavenging are significantly associated with the propensity of a bacterial isolate to cause extra-intestinal infections. Taking advantage of previously generated growth data on a subset of the strains and its correlation to virulence we generated hypothesis on the relationship between iron scavenging and growth in the presence of various antimicrobials, which could have implications for developing new treatment strategies.

Performance and Application of 16S rRNA Gene Cycle Sequencing for Routine Identification of Bacteria in the Clinical Microbiology Laboratory

This review provides a state-of-the-art description of the performance of Sanger cycle sequencing of the 16S rRNA gene for routine identification of bacteria in the clinical microbiology laboratory. A detailed description of the technology and current methodology is outlined with a major focus on proper data analyses and interpretation of sequences. The remainder of the article is focused on a comprehensive evaluation of the application of this method for identification of bacterial pathogens based on analyses of 16S multialignment sequences. In particular, the existing limitations of similarity within 16S for genus- and species-level differentiation of clinically relevant pathogens and the lack of sequence data currently available in public databases is highlighted. A multiyear experience is described of a large regional clinical microbiology service with direct 16S broad-range PCR followed by cycle sequencing for direct detection of pathogens in appropriate clinical samples. The ability of proteomics (matrix-assisted desorption ionization-time of flight) versus 16S sequencing for bacterial identification and genotyping is compared. Finally, the potential for whole-genome analysis by next-generation sequencing (NGS) to replace 16S sequencing for routine diagnostic use is presented for several applications, including the barriers that must be overcome to fully implement newer genomic methods in clinical microbiology. A future challenge for large clinical, reference, and research laboratories, as well as for industry, will be the translation of vast amounts of accrued NGS microbial data into convenient algorithm testing schemes for various applications (i.e., microbial identification, genotyping, and metagenomics and microbiome analyses) so that clinically relevant information can be reported to physicians in a format that is understood and actionable. These challenges will not be faced by clinical microbiologists alone but by every scientist involved in a domain where natural diversity of genes and gene sequences plays a critical role in disease, health, pathogenicity, epidemiology, and other aspects of life-forms. Overcoming these challenges will require global multidisciplinary efforts across fields that do not normally interact with the clinical arena to make vast amounts of sequencing data clinically interpretable and actionable at the bedside.

Microbial genomic island discovery, visualization and analysis

Horizontal gene transfer (also called lateral gene transfer) is a major mechanism for microbial genome evolution, enabling rapid adaptation and survival in specific niches. Genomic islands (GIs), commonly defined as clusters of bacterial or archaeal genes of probable horizontal origin, are of particular medical, environmental and/or industrial interest, as they disproportionately encode virulence factors and some antimicrobial resistance genes and may harbor entire metabolic pathways that confer a specific adaptation (solvent resistance, symbiosis properties, etc). As large-scale analyses of microbial genomes increases, such as for genomic epidemiology investigations of infectious disease outbreaks in public health, there is increased appreciation of the need to accurately predict and track GIs. Over the past decade, numerous computational tools have been developed to tackle the challenges inherent in accurate GI prediction. We review here the main types of GI prediction methods and discuss their advantages and limitations for a routine analysis of microbial genomes in this era of rapid whole-genome sequencing. An assessment is provided of 20 GI prediction software methods that use sequence-composition bias to identify the GIs, using a reference GI data set from 104 genomes obtained using an independent comparative genomics approach. Finally, we present guidelines to assist researchers in effectively identifying these key genomic regions.

The Mycobiome in Health and Disease: Emerging Concepts, Methodologies and Challenges

Fungal disease is an increasingly recognised global clinical challenge associated with high mortality. Early diagnosis of fungal infection remains problematic due to the poor sensitivity and specificity of current diagnostic modalities. Advances in sequencing technologies hold promise in addressing these shortcomings and for improved fungal detection and identification. To translate such emerging approaches into mainstream clinical care will require refinement of current sequencing and analytical platforms, ensuring standardisation and consistency through robust clinical benchmarking and its validation across a range of patient populations. In this state-of-the-art review, we discuss current diagnostic and therapeutic challenges associated with fungal disease and provide key examples where the application of sequencing technologies has potential diagnostic application in assessing the human ‘mycobiome’. We assess how ready access to fungal sequencing may be exploited in broadening our insight into host–fungal interaction, providing scope for clinical diagnostics and the translation of emerging mycobiome research into clinical practice.

A systematic sequencing-based approach for microbial contaminant detection and functional inference

Background

Microbial contamination poses a major difficulty for successful data analysis in biological and biomedical research. Computational approaches utilizing next-generation sequencing (NGS) data offer promising diagnostics to assess the presence of contaminants. However, as host cells are often contaminated by multiple microorganisms, these approaches require careful attention to intra- and interspecies sequence similarities, which have not yet been fully addressed.

Results

We present a computational approach that rigorously investigates the genomic origins of sequenced reads, including those mapped to multiple species that have been discarded in previous studies. Through the analysis of large-scale synthetic and public NGS samples, we estimate that 1000–100,000 contaminating microbial reads are detected per million host reads sequenced by RNA-seq. The microbe catalog we established included Cutibacterium as a prevalent contaminant, suggesting that contamination mostly originates from the laboratory environment. Importantly, by applying a systematic method to infer the functional impact of contamination, we revealed that host-contaminant interactions cause profound changes in the host molecular landscapes, as exemplified by changes in inflammatory and apoptotic pathways during Mycoplasma infection of lymphoma cells.

Conclusions

We provide a computational method for profiling microbial contamination on NGS data and suggest that sources of contamination in laboratory reagents and the experimental environment alter the molecular landscape of host cells leading to phenotypic changes. These findings reinforce the concept that precise determination of the origins and functional impacts of contamination is imperative for quality research and illustrate the usefulness of the proposed approach to comprehensively characterize contamination landscapes.

Electronic supplementary material

The online version of this article (10.1186/s12915-019-0690-0) contains supplementary material, which is available to authorized users.

Using Genomics to Track Global Antimicrobial Resistance

The recent advancements in rapid and affordable DNA sequencing technologies have revolutionized diagnostic microbiology and microbial surveillance. The availability of bioinformatics tools and online accessible databases has been a prerequisite for this. We conducted a scientific literature review and here we present a description of examples of available tools and databases for antimicrobial resistance (AMR) detection and provide future perspectives and recommendations. At least 47 freely accessible bioinformatics resources for detection of AMR determinants in DNA or amino acid sequence data have been developed to date. These include, among others but not limited to, ARG-ANNOT, CARD, SRST2, MEGARes, Genefinder, ARIBA, KmerResistance, AMRFinder, and ResFinder. Bioinformatics resources differ for several parameters including type of accepted input data, presence/absence of software for search within a database of AMR determinants that can be specific to a tool or cloned from other resources, and for the search approach employed, which can be based on mapping or on alignment. As a consequence, each tool has strengths and limitations in sensitivity and specificity of detection of AMR determinants and in application, which for some of the tools have been highlighted in benchmarking exercises and scientific articles. The identified tools are either available at public genome data centers, from GitHub or can be run locally. NCBI and European Nucleotide Archive (ENA) provide possibilities for online submission of both sequencing and accompanying phenotypic antimicrobial susceptibility data, allowing for other researchers to further analyze data, and develop and test new tools. The advancement in whole genome sequencing and the application of online tools for real-time detection of AMR determinants are essential to identify control and prevention strategies to combat the increasing threat of AMR. Accessible tools and DNA sequence data are expanding, which will allow establishing global pathogen surveillance and AMR tracking based on genomics. There is however, a need for standardization of pipelines and databases as well as phenotypic predictions based on the data.

Improved genomic island predictions with IslandPath-DIMOB

Motivation

Genomic islands (GIs) are clusters of genes of probable horizontal origin that play a major role in bacterial and archaeal genome evolution and microbial adaptability. They are of high medical and industrial interest, due to their enrichment in virulence factors, some antimicrobial resistance genes and adaptive metabolic pathways. The development of more sensitive but precise prediction tools, using either sequence composition-based methods or comparative genomics, is needed as large-scale analyses of microbial genomes increase.

Results

IslandPath-DIMOB, a leading GI prediction tool in the IslandViewer webserver, has now been significantly improved by modifying both the decision algorithm to determine sequence composition biases, and the underlying database of HMM profiles for associated mobility genes. The accuracy of IslandPath-DIMOB and other major software has been assessed using a reference GI dataset predicted by comparative genomics, plus a manually curated dataset from literature review. Compared to the previous version (v0.2.0), this IslandPath-DIMOB v1.0.0 achieves 11.7% and 5.3% increase in recall and precision, respectively. IslandPath-DIMOB has the highest Matthews correlation coefficient among individual prediction methods tested, combining one of the highest recall measures (46.9%) at high precision (87.4%). The only method with higher recall had notably lower precision (55.1%). This new IslandPath-DIMOB v1.0.0 will facilitate more accurate studies of GIs, including their key roles in microbial adaptability of medical, environmental and industrial interest.

Availability and implementation

IslandPath-DIMOB v1.0.0 is freely available through the IslandViewer webserver {{http://www.pathogenomics.sfu.ca/islandviewer/}} and as standalone software {{https://github.com/brinkmanlab/islandpath/}} under the GNU-GPLv3.

Supplementary information

Supplementary data are available at Bioinformatics online.

Pan-Genomic and Polymorphic Driven Prediction of Antibiotic Resistance in Elizabethkingia

The Elizabethkingia are a genetically diverse genus of emerging pathogens that exhibit multidrug resistance to a range of common antibiotics. Two representative species, Elizabethkingia bruuniana and E. meningoseptica, were phenotypically tested to determine minimum inhibitory concentrations (MICs) for five antibiotics. Ultra-long read sequencing with Oxford Nanopore Technologies (ONT) and subsequent de novo assembly produced complete, gapless circular genomes for each strain. Alignment based annotation with Prokka identified 5,480 features in E. bruuniana and 5,203 features in E. meningoseptica, where none of these identified genes or gene combinations corresponded to observed phenotypic resistance values. Pan-genomic analysis, performed with an additional 19 Elizabethkingia strains, identified a core-genome size of 2,658,537 bp, 32 uniquely identifiable intrinsic chromosomal antibiotic resistance core-genes and 77 antibiotic resistance pan-genes. Using core-SNPs and pan-genes in combination with six machine learning (ML) algorithms, binary classification of clindamycin and vancomycin resistance achieved f1 scores of 0.94 and 0.84, respectively. Performance on the more challenging multiclass problem for fusidic acid, rifampin and ciprofloxacin resulted in f1 scores of 0.70, 0.75, and 0.54, respectively. By producing two sets of quality biological predictors, pan-genome genes and core-genome SNPs, from long-read sequence data and applying an ensemble of ML techniques, our results demonstrated that accurate phenotypic inference, at multiple AMR resolutions, can be achieved.

Pulsed-field gel electrophoresis (PFGE): A review of the "gold standard" for bacteria typing and current alternatives

Pulsed-field gel electrophoresis (PFGE) is considered the "gold standard" for bacteria typing. The method involves enzyme restriction of bacteria DNA, separation of the restricted DNA bands using a pulsed-field electrophoresis chamber, followed by clonal assignment of bacteria based on PFGE banding patterns. Various PFGE protocols have been developed for typing different bacteria, leading it to be one of the most widely used methods for phylogenetic studies, food safety surveillance, infection control and outbreak investigations. On the other hand, as PFGE is lengthy and labourious, several PCR-based typing methods can be used as alternatives for research purposes. Recently, matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and whole genome sequencing (WGS) have also been proposed for bacteria typing. In fact, as WGS provides more information, such as antimicrobial resistance and virulence of the tested bacteria in comparison to PFGE, more and more laboratories are currently transitioning from PFGE to WGS for bacteria typing. Nevertheless, PFGE will remain an affordable and relevant technique for small laboratories and hospitals in years to come.

Investing in Food Safety for Developing Countries: Opportunities and Challenges in Applying Whole-Genome Sequencing for Food Safety Management

Whole-genome sequencing (WGS) has become a significant tool in investigating foodborne disease outbreaks and some countries have incorporated WGS into national food control systems. However, WGS poses technical challenges that deter developing countries from incorporating it into their food safety management system. A rapid scoping review was conducted, followed by a focus group session, to understand the current situation regarding the use of WGS for foodborne disease surveillance and food monitoring at the global level and identify key limiting factors for developing countries in adopting WGS for their food control systems. The results showed that some developed nations routinely use WGS in their food surveillance systems resulting in more precise understanding of the causes of outbreaks. In developing nations, knowledge of WGS exists in the academic/research sectors; however, there is limited understanding at the government level regarding the usefulness of WGS for food safety regulatory activities. Thus, incorporation of WGS is extremely limited in most developing nations. While some countries lack the capacity to collect and analyze the data generated from WGS, the most significant technical gap in most developing countries is in data interpretation using bioinformatics. The gaps in knowledge and capacities between developed and developing nations regarding use of WGS likely introduce an inequality in international food trade, and thus, relevant international organizations, as well as the countries that are already proficient in the use of WGS, have significant roles in assisting developing nations to be able to fully benefit from the technology and its applications in food safety management.

Operational models and criteria for incorporating microbial whole genome sequencing in hospital microbiology - A systematic literature review

BACKGROUND

Microbial whole genome sequencing (WGS) has many advantages over standard microbiological methods. However, it is not yet widely implemented in routine hospital diagnostics due to notable challenges.

OBJECTIVES

The aim was to extract managerial, financial and clinical criteria supporting the decision to implement WGS in routine diagnostic microbiology, across different operational models of implementation in the hospital setting.

METHODS

This was a systematic review of literature identified through PubMed and Web of Science. English literature studies discussing the applications of microbial WGS without limitation on publication date were eligible. A narrative approach for categorization and synthesis of the sources identified was adopted.

RESULTS

A total of 98 sources were included. Four main alternative operational models for incorporating WGS in clinical microbiology laboratories were identified: full in-house sequencing and analysis, full outsourcing of sequencing and analysis and two hybrid models combining in-house/outsourcing of the sequencing and analysis components. Six main criteria (and multiple related sub-criteria) for WGS implementation emerged from our review and included cost (e.g. the availability of resources for capital and operational investment); manpower (e.g. the ability to provide training programmes or recruit trained personnel), laboratory infrastructure (e.g. the availability of supplies and consumables or sequencing platforms), bioinformatics requirements (e.g. the availability of valid analysis tools); computational infrastructure (e.g. the availability of storage space or data safety arrangements); and quality control (e.g. the existence of standardized procedures).

CONCLUSIONS

The decision to incorporate WGS in routine diagnostics involves multiple, sometimes competing, criteria and sub-criteria. Mapping these criteria systematically is an essential stage in developing policies for adoption of this technology, e.g. using a multicriteria decision tool. Future research that will prioritize criteria and sub-criteria that were identified in our review in the context of operational models will inform decision-making at clinical and managerial levels with respect to effective implementation of WGS for routine use. Beyond WGS, similar decision-making challenges are expected with respect to future integration of clinical metagenomics.

Direct Diagnostic Tests for Lyme Disease

Borrelia burgdorferi was discovered to be the cause of Lyme disease in 1983, leading to seroassays. The 1994 serodiagnostic testing guidelines predated a full understanding of key B. burgdorferi antigens and have a number of shortcomings. These serologic tests cannot distinguish active infection, past infection, or reinfection. Reliable direct-detection methods for active B. burgdorferi infection have been lacking in the past but are needed and appear achievable. New approaches have effectively been applied to other emerging infections and show promise in direct detection of B. burgdorferi infections.

Nanopore ultra-long read sequencing technology for antimicrobial resistance detection in Mannheimia haemolytica

Disruptive innovations in long-range, cost-effective direct template nucleic acid sequencing are transforming clinical and diagnostic medicine. A multidrug resistant strain and a pan-susceptible strain of Mannheimia haemolytica, isolated from pneumonic bovine lung samples, were sequenced at 146× and 111× coverage, respectively with Oxford Nanopore Technologies MinION. De novo assembly produced a complete genome for the non-resistant strain and a nearly complete assembly for the drug resistant strain. Functional annotation using RAST (Rapid Annotations using Subsystems Technology), CARD (Comprehensive Antibiotic Resistance Database) and ResFinder databases identified genes conferring resistance to different classes of antibiotics including β-lactams, tetracyclines, lincosamides, phenicols, aminoglycosides, sulfonamides and macrolides. Resistance phenotypes of the M. haemolytica strains were determined by minimum inhibitory concentration (MIC) of the antibiotics. Sequencing with a highly portable MinION device corresponded to MIC assays with most of the antimicrobial resistant determinants being identified with as few as 5437 reads, except for the genes responsible for resistance to Fluoroquinolones. The resulting quality assemblies and AMR gene annotation highlight the efficiency of ultra-long read, whole-genome sequencing (WGS) as a valuable tool in diagnostic veterinary medicine.

Exploring bacterial resistome and resistance dessemination: an approach of whole genome sequencing

For several decades antibiotics are used to combat against pathogenic bacteria, but their misuse and overuse have caused the emergence of resistant bacteria. The scarcities of effective antibiotics along with unavailability of alternative solutions have exacerbated bacterial infections and mortality rate. This review provides the concept of bacterial resistome and mechanisms of resistance. It has also described the utility of whole genome sequencing in identifying resistance and its dissemination in association with available bioinformatics tools and databases. Moreover, the whole genome sequencing methodology described in this review will help to select effective antibiotics, maintain unparalleled surveillance of resistance and provide early diagnosis during resistance outbreaks. The provided information could be used to control infection caused by resistant microorganisms.

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.

Genomic epidemiology of multidrug-resistant Gram-negative organisms

The emergence and spread of antibiotic-resistant Gram-negative bacteria (rGNB) across global healthcare networks presents a significant threat to public health. As the number of effective antibiotics available to treat these resistant organisms dwindles, it is essential that we devise more effective strategies for controlling their proliferation. Recently, whole-genome sequencing has emerged as a disruptive technology that has transformed our understanding of the evolution and epidemiology of diverse rGNB species, and it has the potential to guide strategies for controlling the evolution and spread of resistance. Here, we review specific areas in which genomics has already made a significant impact, including outbreak investigations, regional epidemiology, clinical diagnostics, resistance evolution, and the study of epidemic lineages. While highlighting early successes, we also point to the next steps needed to translate this technology into strategies to improve public health and clinical medicine.

Rapid analysis of metagenomic data using signature-based clustering

Background

Sequencing highly-variable 16S regions is a common and often effective approach to the study of microbial communities, and next-generation sequencing (NGS) technologies provide abundant quantities of data for analysis. However, the speed of existing analysis pipelines may limit our ability to work with these quantities of data. Furthermore, the limited coverage of existing 16S databases may hamper our ability to characterise these communities, particularly in the context of complex or poorly studied environments.

Results

In this article we present the SigClust algorithm, a novel clustering method involving the transformation of sequence reads into binary signatures. When compared to other published methods, SigClust yields superior cluster coherence and separation of metagenomic read data, while operating within substantially reduced timeframes. We demonstrate its utility on published Illumina datasets and on a large collection of labelled wound reads sourced from patients in a wound clinic. The temporal analysis is based on tracking the dominant clusters of wound samples over time. The analysis can identify markers of both healing and non-healing wounds in response to treatment. Prominent clusters are found, corresponding to bacterial species known to be associated with unfavourable healing outcomes, including a number of strains of Staphylococcus aureus.

Conclusions

SigClust identifies clusters rapidly and supports an improved understanding of the wound microbiome without reliance on a reference database. The results indicate a promising use for a SigClust-based pipeline in wound analysis and prediction, and a possible novel method for wound management and treatment.

Proteotyping bacteria: Characterization, differentiation and identification of pneumococcus and other species within the Mitis Group of the genus Streptococcus by tandem mass spectrometry proteomics

A range of methodologies may be used for analyzing bacteria, depending on the purpose and the level of resolution needed. The capability for recognition of species distinctions within the complex spectrum of bacterial diversity is necessary for progress in microbiological research. In clinical settings, accurate, rapid and cost-effective methods are essential for early and efficient treatment of infections. Characterization and identification of microorganisms, using, bottom-up proteomics, or "proteotyping", relies on recognition of species-unique or associated peptides, by tandem mass spectrometry analyses, dependent upon an accurate and comprehensive foundation of genome sequence data, allowing for differentiation of species, at amino acid-level resolution. In this study, the high resolution and accuracy of MS/MS-based proteotyping was demonstrated, through analyses of the three phylogenetically and taxonomically most closely-related species of the Mitis Group of the genus Streptococcus: i.e., the pathogenic species, Streptococcus pneumoniae (pneumococcus), and the commensal species, Streptococcus pseudopneumoniae and Streptococcus mitis. To achieve high accuracy, a genome sequence database used for matching peptides was created and carefully curated. Here, MS-based, bottom-up proteotyping was observed and confirmed to attain the level of resolution necessary for differentiating and identifying the most-closely related bacterial species, as demonstrated by analyses of species of the Streptococcus Mitis Group, even when S. pneumoniae were mixed with S. pseudopneumoniae and S. mitis, by matching and identifying more than 200 unique peptides for each species.

From Theory to Practice: Translating Whole-Genome Sequencing (WGS) into the Clinic

Hospitals worldwide are facing an increasing incidence of hard-to-treat infections. Limiting infections and providing patients with optimal drug regimens require timely strain identification as well as virulence and drug-resistance profiling. Additionally, prophylactic interventions based on the identification of environmental sources of recurrent infections (e.g., contaminated sinks) and reconstruction of transmission chains (i.e., who infected whom) could help to reduce the incidence of nosocomial infections. WGS could hold the key to solving these issues. However, uptake in the clinic has been slow. Some major scientific and logistical challenges need to be solved before WGS fulfils its potential in clinical microbial diagnostics. In this review we identify major bottlenecks that need to be resolved for WGS to routinely inform clinical intervention and discuss possible solutions.

Evaluation of whole genome sequencing and software tools for drug susceptibility testing of Mycobacterium tuberculosis

OBJECTIVES

Culture-based assays are currently the reference standard for drug susceptibility testing for Mycobacterium tuberculosis. They provide good sensitivity and specificity but are time consuming. The objective of this study was to evaluate whether whole genome sequencing (WGS), combined with software tools for data analysis, can replace routine culture-based assays for drug susceptibility testing of M. tuberculosis.

METHODS

M. tuberculosis cultures sent to the Finnish mycobacterial reference laboratory in 2014 (n = 211) were phenotypically tested by Mycobacteria Growth Indicator Tube (MGIT) for first-line drug susceptibilities. WGS was performed for all isolates using the Illumina MiSeq system, and data were analysed using five software tools (PhyResSE, Mykrobe Predictor, TB Profiler, TGS-TB and KvarQ). Diagnostic time and reagent costs were estimated for both methods.

RESULTS

The sensitivity of the five software tools to predict any resistance among strains was almost identical, ranging from 74% to 80%, and specificity was more than 95% for all software tools except for TGS-TB. The sensitivity and specificity to predict resistance to individual drugs varied considerably among the software tools. Reagent costs for MGIT and WGS were €26 and €143 per isolate respectively. Turnaround time for MGIT was 19 days (range 10-50 days) for first-line drugs, and turnaround time for WGS was estimated to be 5 days (range 3-7 days).

CONCLUSIONS

WGS could be used as a prescreening assay for drug susceptibility testing with confirmation of resistant strains by MGIT. The functionality and ease of use of the software tools need to be improved.

Simple and label-free pathogen enrichment via homobifunctional imidoesters using a microfluidic (SLIM) system for ultrasensitive pathogen detection in various clinical specimens

Diseases caused by pathogenic microorganisms including bacteria and viruses can cause serious medical issues including death and result in huge economic losses. Despite the myriad of recent advances in the rapid and accurate detection of pathogens, large volume clinical samples with a low concentration of pathogens continue to present challenges for diagnosis and surveillance. We here report a simple and label-free approach via homobifunctional imidoesters (HIs) with a microfluidic platform (SLIM) to efficiently enrich and extract pathogens at low concentrations from clinical samples. The SLIM system consists of an assembled double microfluidic chip for streamlining large volume processing and HIs for capturing pathogens and isolating nucleic acids by both electrostatic and covalent interaction without a chaotropic detergent or bulky instruments. The SLIM system significantly increases the enrichment and extraction rate of pathogens (up to 80% at 10 CFU (colony forming unit) in a 1 mL volume within 50 min). We demonstrated its clinical utility in large sample volumes from 46 clinical specimens including environmental swabs, saliva, and blood plasma. The SLIM system showed higher sensitivity with these samples and could detect pathogens that were below the threshold of detection with other methods. Finally, by combining our SLIM approach with an isothermal optical sensor, pathogens could be detected at a very high sensitivity in blood plasma samples within 80 min via enrichment, extraction and detection steps. Our SLIM system thus provides a simple, reliable, cost-effective and ultrasensitive pathogen diagnosis platform for use with large volume clinical samples and would thus have significant utility for various infectious diseases.

•

SLIM system significantly increases the enrichment and extraction rate of pathogens.

•

Demonstrated its clinical utility in large sample volumes from 46 clinical specimens.

•

A simple, reliable, cost-effective and ultrasensitive pathogen diagnosis platform.

DNA extraction from primary liquid blood cultures for bloodstream infection diagnosis using whole genome sequencing

PURPOSE

Speed of bloodstream infection diagnosis is vital to reduce morbidity and mortality. Whole genome sequencing (WGS) performed directly from liquid blood culture could provide single-assay species and antibiotic susceptibility prediction; however, high inhibitor and human cell/DNA concentrations limit pathogen recovery. We develop a method for the preparation of bacterial DNA for WGS-based diagnostics direct from liquid blood culture.

METHODOLOGY

We evaluate three commercial DNA extraction kits: BiOstic Bacteraemia, Amplex Hyplex and MolYsis Plus. Differential centrifugation, filtration, selective lysis and solid-phase reversible immobilization bead clean-up are tested to improve human cells/DNA and inhibitor removal. Using WGS (Illumina/MinION), we assess human DNA removal, pathogen recovery, and predict species and antibiotic susceptibility inpositive blood cultures of 44 Gram-negative and 54 Staphylococcus species.Results/Key findings. BiOstic kit extractions yield the greatest mean DNA concentration, 94-301 ng µl^-1, versus 0-2.5 ng µl^-1 using Amplex and MolYsis kits. However, we note higher levels of inhibition (260/280 ratio 0.9-2.1) and human DNA (0.0-4.4×10⁶ copies) in BiOstic extracts. Differential centrifugation (2000 g, 1 min) prior to BiOstic extraction reduces human DNA by 63-89 % with selective lysis minimizing by a further 62 %. Post-extraction bead clean-up lowers inhibition. Overall, 67 % of sequenced samples (Illumina MiSeq) contain <10 % human DNA, with >93 % concordance between WGS-based species and susceptibility predictions and clinical diagnosis. If >60 % of sequencing reads are human (7/98 samples) susceptibility prediction becomes compromised. Novel MinION-based WGS (n=9) currently gives rapid species identification but not susceptibility prediction.

CONCLUSION

Our method for DNA preparation allows WGS-based diagnosis direct from blood culture bottles, providing species and antibiotic susceptibility prediction in a single assay.

Diagnostics and laboratory role in outbreaks

PURPOSE OF REVIEW

The review describes the investigative benefits of traditional and novel molecular epidemiology techniques, while acknowledging the limitations faced by clinical laboratories seeking to implement these methods.

RECENT FINDINGS

Pulse-field gel electrophoresis and other traditional techniques remain powerful tools in outbreak investigations and continue to be used by multiple groups. Newer techniques such as matrix-assisted laser desorption/ionization-time of flight mass-spectrometry and whole genome sequencing show great promise. However, there is a lack of standardization regarding definitions for genetic relatedness, nor are there established criteria for accuracy and reproducibility. There are also challenges regarding availability of trained bioinformatics staff, and concerns regarding reimbursement.

SUMMARY

There are many tools available for molecular epidemiologic investigation. Epidemiologists and clinical laboratorians should work together to determine which testing methods are best for each institution.

MICRA: an automatic pipeline for fast characterization of microbial genomes from high-throughput sequencing data

The increase in available sequence data has advanced the field of microbiology; however, making sense of these data without bioinformatics skills is still problematic. We describe MICRA, an automatic pipeline, available as a web interface, for microbial identification and characterization through reads analysis. MICRA uses iterative mapping against reference genomes to identify genes and variations. Additional modules allow prediction of antibiotic susceptibility and resistance and comparing the results of several samples. MICRA is fast, producing few false-positive annotations and variant calls compared to current methods, making it a tool of great interest for fully exploiting sequencing data.

Synthetic Biology-Based Point-of-Care Diagnostics for Infectious Disease

Infectious diseases outpace all other causes of death in low-income countries, posing global health risks, laying stress on healthcare systems and societies, and taking an avoidable human toll. One solution to this crisis is early diagnosis of infectious disease, which represents a powerful way to optimize treatment, increase patient survival rate, and decrease healthcare costs. However, conventional early diagnosis methods take a long time to generate results, lack accuracy, and are known to seriously underperform with regard to fungal and viral infections. Synthetic biology offers a fast and highly accurate alternative to conventional infectious disease diagnosis. In this review, we outline obstacles to infectious disease diagnostics and discuss two emerging alternatives: synthetic viral diagnostic systems and biosensors. We argue that these synthetic biology-based approaches may overcome diagnostic obstacles in infectious disease and improve health outcomes.

Practical issues in implementing whole-genome-sequencing in routine diagnostic microbiology

BACKGROUND

Next generation sequencing (NGS) is increasingly being used in clinical microbiology. Like every new technology adopted in microbiology, the integration of NGS into clinical and routine workflows must be carefully managed.

AIM

To review the practical aspects of implementing bacterial whole genome sequencing (WGS) in routine diagnostic laboratories.

SOURCES

Review of the literature and expert opinion.

CONTENT

In this review, we discuss when and how to integrate whole genome sequencing (WGS) in the routine workflow of the clinical laboratory. In addition, as the microbiology laboratories have to adhere to various national and international regulations and criteria for their accreditation, we deliberate on quality control issues for using WGS in microbiology, including the importance of proficiency testing. Furthermore, the current and future place of this technology in the diagnostic hierarchy of microbiology is described as well as the necessity of maintaining backwards compatibility with already established methods. Finally, we speculate on the question of whether WGS can entirely replace routine microbiology in the future and the tension between the fact that most sequencers are designed to process multiple samples in parallel whereas for optimal diagnosis a one-by-one processing of the samples is preferred. Special reference is made to the cost and turnaround time of WGS in diagnostic laboratories.

IMPLICATIONS

Further development is required to improve the workflow for WGS, in particular to shorten the turnaround time, reduce costs, and streamline downstream data analyses. Only when these processes reach maturity will reliance on WGS for routine patient management and infection control management become feasible, enabling the transformation of clinical microbiology into a genome-based and personalized diagnostic field.

MetaMeta: integrating metagenome analysis tools to improve taxonomic profiling

BACKGROUND

Many metagenome analysis tools are presently available to classify sequences and profile environmental samples. In particular, taxonomic profiling and binning methods are commonly used for such tasks. Tools available among these two categories make use of several techniques, e.g., read mapping, k-mer alignment, and composition analysis. Variations on the construction of the corresponding reference sequence databases are also common. In addition, different tools provide good results in different datasets and configurations. All this variation creates a complicated scenario to researchers to decide which methods to use. Installation, configuration and execution can also be difficult especially when dealing with multiple datasets and tools.

RESULTS

We propose MetaMeta: a pipeline to execute and integrate results from metagenome analysis tools. MetaMeta provides an easy workflow to run multiple tools with multiple samples, producing a single enhanced output profile for each sample. MetaMeta includes a database generation, pre-processing, execution, and integration steps, allowing easy execution and parallelization. The integration relies on the co-occurrence of organisms from different methods as the main feature to improve community profiling while accounting for differences in their databases.

CONCLUSIONS

In a controlled case with simulated and real data, we show that the integrated profiles of MetaMeta overcome the best single profile. Using the same input data, it provides more sensitive and reliable results with the presence of each organism being supported by several methods. MetaMeta uses Snakemake and has six pre-configured tools, all available at BioConda channel for easy installation (conda install -c bioconda metameta). The MetaMeta pipeline is open-source and can be downloaded at: https://gitlab.com/rki_bioinformatics .

Diagnosis of Sepsis with Cell-free DNA by Next-Generation Sequencing Technology in ICU Patients

BACKGROUND AND AIMS

Bacteremia is a common serious manifestation of disease in the intensive care unit (ICU), which requires quick and accurate determinations of pathogens to select the appropriate antibiotic treatment. To overcome the shortcomings of traditional bacterial culture (BC), we have adapted next-generation sequencing (NGS) technology to identify pathogens from cell-free plasma DNA.

METHODS

In this study, 78 plasma samples from ICU patients were analyzed by both NGS and BC methods and verified by PCR amplification/Sanger sequencing and ten plasma samples from healthy volunteers were analyzed by NGS as negative controls to define or calibrate the threshold of the NGS methodology.

RESULTS

Overall, 1578 suspected patient samples were found to contain bacteria or fungi by NGS, whereas ten patients were diagnosed by BC. Seven samples were diagnosed with bacterial or fungal infection both by NGS and BC. Among them, two samples were diagnosed with two types of bacteria by NGS, whereas one sample was diagnosed with two types of bacteria by BC, which increased the detectability of bacteria or fungi from 11 with BC to 17 with NGS. Most interestingly, 14 specimens were also diagnosed with viral infection by NGS. The overall diagnostic sensitivity was significantly increased from 12.82% (10/78) by BC alone to 30.77% (24/78) by NGS alone for ICU patients, which provides more useful information for establishing patient treatment plans.

CONCLUSION

NGS technology can be applied to detect bacteria in clinical blood samples as an emerging diagnostic tool rich in information to determine the appropriate treatment of septic patients.