Stability of the gut microbiota in persons with paediatric-onset multiple sclerosis and related demyelinating diseases.

OBJECTIVE: Examine if the gut microbiota composition changes across repeated samples in paediatric-onset multiple sclerosis (MS) or monophasic-acquired demyelinating syndromes (monoADS). METHODS: A total of 36 individuals (18 MS/18 monoADS) with ⩾2 stool samples were included. Stool sample-derived DNA was sequenced. Alpha/beta diversities and genus-level taxa were analysed. RESULTS: Mean ages at first sample procurement (MS/monoADS) = 18.0/13.8 years. Median time (months) between first/second samples = 11.2 and second/third = 10.3. Alpha/beta diversities did not differ between stool samples (p > 0.09), while one genus - Solobacterium did (p = 0.001). CONCLUSIONS: The gut microbiota composition in paediatric-onset MS and monoADS exhibited stability, suggesting that single stool sample procurement is a reasonable first approach.

Colorectal Cancer Screening in Inflammatory Bowel Diseases-Can Characterization of GI Microbiome Signatures Enhance Neoplasia Detection?

Current noninvasive methods for colorectal cancer (CRC) screening are not optimized for persons with inflammatory bowel diseases (IBDs), requiring patients to undergo frequent interval screening via colonoscopy. Although colonoscopy-based screening reduces CRC incidence in IBD patients, rates of interval CRC remain relatively high, highlighting the need for more targeted approaches. In recent years, the discovery of disease-specific microbiome signatures for both IBD and CRC has begun to emerge, suggesting that stool-based biomarker detection using metagenomics and other culture-independent technologies may be useful for personalized, early, noninvasive CRC screening in IBD patients. Here we discuss the utility of the stool microbiome as a noninvasive CRC screening tool. Comparing the performance of multiple microbiome-based CRC classifiers, including several multi-cohort meta-analyses, we find that noninvasive detection of colorectal adenomas and carcinomas from microbial biomarkers is an active area of study with promising early results.

The gut microbiota in pediatric multiple sclerosis and demyelinating syndromes.

OBJECTIVE: To examine the gut microbiota in individuals with and without pediatric-onset multiple sclerosis (MS). METHODS: We compared stool-derived microbiota of Canadian Pediatric Demyelinating Disease Network study participants ≤21 years old, with MS (disease-modifying drug [DMD] exposed and naïve) or monophasic acquired demyelinating syndrome [monoADS] (symptom onset <18 years), and unaffected controls. All were ≥30 days without antibiotics or corticosteroids. V4 region 16S RNA gene-derived amplicon sequence variants (Illumina MiSeq) were assessed using negative binomial regression and network analyses; rate ratios were age- and sex-adjusted (aRR). RESULTS: Thirty-two MS, 41 monoADS (symptom onset [mean] = 14.0 and 6.9 years) and 36 control participants were included; 75%/56%/58% were female, with mean ages at stool sample = 16.5/13.8/15.1 years, respectively. Nine MS cases (28%) were DMD-naïve. Although microbiota diversity (alpha, beta) did not differ between participants (p > 0.1), taxa-level and gut community networks did. MS (vs. monoADS) exhibited > fourfold higher relative abundance of the superphylum Patescibacteria (aRR = 4.2;95%CI:1.6-11.2, p = 0.004, Q = 0.01), and lower abundances of short-chain fatty acid (SCFA)-producing Lachnospiraceae (Anaerosporobacter) and Ruminococcaceae (p, Q < 0.05). DMD-naïve MS cases were depleted for Clostridiales vadin-BB60 (unnamed species) versus either DMD-exposed, controls (p, Q < 0.01), or monoADS (p = 0.001, Q = 0.06) and exhibited altered community connectedness (p < 10-9 Kruskal-Wallis), with SCFA-producing taxa underrepresented. Consistent taxa-level findings from an independent US Network of Pediatric MS Centers case/control (n = 51/42) cohort included >eightfold higher abundance for Candidatus Stoquefichus and Tyzzerella (aRR = 8.8-12.8, p < 0.05) in MS cases and 72%-80% lower abundance of SCFA-producing Ruminococcaceae-NK4A214 (aRR = 0.38-0.2, p ≤ 0.01). INTERPRETATION: Gut microbiota community structure, function and connectivity, and not just individual taxa, are of likely importance in MS.

Microbiome-Mediated Immune Signaling in Inflammatory Bowel Disease and Colorectal Cancer: Support From Meta-omics Data.

Chronic intestinal inflammation and microbial dysbiosis are hallmarks of colorectal cancer (CRC) and inflammatory bowel diseases (IBD), such as Crohn's disease and ulcerative colitis. However, the mechanistic relationship between gut dysbiosis and disease has not yet been fully characterized. Although the "trigger" of intestinal inflammation remains unknown, a wealth of evidence supports the role of the gut microbiome as a mutualistic pseudo-organ that significantly influences intestinal homeostasis and is capable of regulating host immunity. In recent years, culture-independent methods for assessing microbial communities as a whole (termed meta-omics) have grown beyond taxonomic identification and genome characterization (metagenomics) into new fields of research that collectively expand our knowledge of microbiomes. Metatranscriptomics, metaproteomics, and metabolomics are meta-omics techniques that aim to describe and quantify the functional activity of the gut microbiome. Uncovering microbial metabolic contributions in the context of IBD and CRC using these approaches provides insight into how the metabolic microenvironment of the GI tract shapes microbial community structure and how the microbiome, in turn, influences the surrounding ecosystem. Immunological studies in germ-free and wild-type mice have described several host-microbiome interactions that may play a role in autoinflammation. Chronic colitis is a precursor to CRC, and changes in the gut microbiome may be an important link triggering the neoplastic process in chronic colitis. In this review, we describe several microbiome-mediated mechanisms of host immune signaling, such as short-chain fatty acid (SCFA) and bile acid metabolism, inflammasome activation, and cytokine regulation in the context of IBD and CRC, and discuss the supporting role for these mechanisms by meta-omics data.

Assessment of Inter-Laboratory Variation in the Characterization and Analysis of the Mucosal Microbiota in Crohn's Disease and Ulcerative Colitis.

BACKGROUND: In studies evaluating the microbiome, numerous factors can contribute to technical variability. These factors include DNA extraction methodology, sequencing protocols, and data analysis strategies. We sought to evaluate the impact these factors have on the results obtained when the sequence data are independently generated and analyzed by different laboratories. METHODS: To evaluate the effect of technical variability, we used human intestinal biopsy samples resected from individuals diagnosed with an inflammatory bowel disease (IBD), including Crohn's disease (n = 12) and ulcerative colitis (n = 10), and those without IBD (n = 10). Matched samples from each participant were sent to three laboratories and studied using independent protocols for DNA extraction, library preparation, targeted-amplicon sequencing of a 16S rRNA gene hypervariable region, and processing of sequence data. We looked at two measures of interest - Bray-Curtis PERMANOVA R 2 values and log2 fold-change estimates of the 25 most-abundant taxa - to assess variation in the results produced by each laboratory, as well the relative contribution to variation from the different extraction, sequencing, and analysis steps used to generate these measures. RESULTS: The R 2 values and estimated differential abundance associated with diagnosis were consistent across datasets that used different DNA extraction and sequencing protocols, and within datasets that pooled samples from multiple protocols; however, variability in bioinformatic processing of sequence data led to changes in R 2 values and inconsistencies in taxonomic assignment and abundance estimates. CONCLUSION: Although the contribution of DNA extraction and sequencing methods to variability were observable, we find that results can be robust to the various extraction and sequencing approaches used in our study. Differences in data processing methods have a larger impact on results, making comparison among studies less reliable and the combined analysis of bioinformatically processed samples nearly impossible. Our results highlight the importance of making raw sequence data available to facilitate combined and comparative analyses of published studies using common data processing protocols. Study methodologies should provide detailed data processing methods for validation, interpretability, reproducibility, and comparability.

A Comparison of Whole Genome Sequencing of SARS-CoV-2 Using Amplicon-Based Sequencing, Random Hexamers, and Bait Capture.

Genome sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is increasingly important to monitor the transmission and adaptive evolution of the virus. The accessibility of high-throughput methods and polymerase chain reaction (PCR) has facilitated a growing ecosystem of protocols. Two differing protocols are tiling multiplex PCR and bait capture enrichment. Each method has advantages and disadvantages but a direct comparison with different viral RNA concentrations has not been performed to assess the performance of these approaches. Here we compare Liverpool amplification, ARTIC amplification, and bait capture using clinical diagnostics samples. All libraries were sequenced using an Illumina MiniSeq with data analyzed using a standardized bioinformatics workflow (SARS-CoV-2 Illumina GeNome Assembly Line; SIGNAL). One sample showed poor SARS-CoV-2 genome coverage and consensus, reflective of low viral RNA concentration. In contrast, the second sample had a higher viral RNA concentration, which yielded good genome coverage and consensus. ARTIC amplification showed the highest depth of coverage results for both samples, suggesting this protocol is effective for low concentrations. Liverpool amplification provided a more even read coverage of the SARS-CoV-2 genome, but at a lower depth of coverage. Bait capture enrichment of SARS-CoV-2 cDNA provided results on par with amplification. While only two clinical samples were examined in this comparative analysis, both the Liverpool and ARTIC amplification methods showed differing efficacy for high and low concentration samples. In addition, amplification-free bait capture enriched sequencing of cDNA is a viable method for generating a SARS-CoV-2 genome sequence and for identification of amplification artifacts.

The Gut Microbiome in Inflammatory Bowel Disease: Lessons Learned From Other Immune-Mediated Inflammatory Diseases.

There is a growing appreciation for the role of the gut microbiome in human health and disease. Aided by advances in sequencing technologies and analytical methods, recent research has shown the healthy gut microbiome to possess considerable diversity and functional capacity. Dysbiosis of the gut microbiota is believed to be involved in the pathogenesis of not only diseases that primarily affect the gastrointestinal tract but also other less obvious diseases, including neurologic, rheumatologic, metabolic, hepatic, and other illnesses. Chronic immune-mediated inflammatory diseases (IMIDs) represent a group of diseases that share many underlying etiological factors including genetics, aberrant immunological responses, and environmental factors. Gut dysbiosis has been reported to be common to IMIDs as a whole, and much effort is currently being directed toward elucidating microbiome-mediated disease mechanisms and their implications for causality. In this review, we discuss gut microbiome studies in several IMIDs and show how these studies can inform our understanding of the role of the gut microbiome in inflammatory bowel disease.

The Gut Microbiome as a Target for IBD Treatment: Are We There Yet?

PURPOSE OF REVIEW: This review aims to highlight recent research on the gut microbiome in IBD and the application of microbiome-modulating therapies for the treatment of IBD including the use of the microbiome as an indicator for disease severity and treatment response. RECENT FINDINGS: Despite the high number of gut microbiome studies and emerging evidence supporting the gut microbiome's involvement in disease pathogenesis, no single microorganism has been identified as a pathogenic agent in IBD. Retrospective studies and meta-analyses on antibiotic use in ulcerative colitis and Crohn's disease and long-term outcomes are conflicting. Similarly, the use of probiotics for the treatment of IBD remains inconclusive; however, some encouraging results are emerging as microbial concoctions are optimized to include beneficial bacterial strains. Fecal microbial transplantation (FMT) is currently emerging as one of the more promising microbiome-modulating IBD therapies. FMT studies in ulcerative colitis have shown improved remission rates compared to placebo; however, relatively small study sample sizes and varied treatment methods, limit definitive conclusions. With clear evidence of an IBD gut dysbiosis, novel therapies to treat and prevent disease relapse will undoubtedly require a microbiome-modulating approach. The complexity and variability of IBD disease pathogenesis (disease phenotype, gut microbiome, host genetic susceptibility, and environmental factors) will likely require a personalized and multidimensional treatment approach where microbiome-modulating therapy is coupled with other therapies to target other IBD disease components.

A comparative study of the gut microbiota in immune-mediated inflammatory diseases-does a common dysbiosis exist?

BACKGROUND: Immune-mediated inflammatory disease (IMID) represents a substantial health concern. It is widely recognized that IMID patients are at a higher risk for developing secondary inflammation-related conditions. While an ambiguous etiology is common to all IMIDs, in recent years, considerable knowledge has emerged regarding the plausible role of the gut microbiome in IMIDs. This study used 16S rRNA gene amplicon sequencing to compare the gut microbiota of patients with Crohn's disease (CD; N = 20), ulcerative colitis (UC; N = 19), multiple sclerosis (MS; N = 19), and rheumatoid arthritis (RA; N = 21) versus healthy controls (HC; N = 23). Biological replicates were collected from participants within a 2-month interval. This study aimed to identify common (or unique) taxonomic biomarkers of IMIDs using both differential abundance testing and a machine learning approach. RESULTS: Significant microbial community differences between cohorts were observed (pseudo F = 4.56; p = 0.01). Richness and diversity were significantly different between cohorts (pFDR < 0.001) and were lowest in CD while highest in HC. Abundances of Actinomyces, Eggerthella, Clostridium III, Faecalicoccus, and Streptococcus (pFDR < 0.001) were significantly higher in all disease cohorts relative to HC, whereas significantly lower abundances were observed for Gemmiger, Lachnospira, and Sporobacter (pFDR < 0.001). Several taxa were found to be differentially abundant in IMIDs versus HC including significantly higher abundances of Intestinibacter in CD, Bifidobacterium in UC, and unclassified Erysipelotrichaceae in MS and significantly lower abundances of Coprococcus in CD, Dialister in MS, and Roseburia in RA. A machine learning approach to classify disease versus HC was highest for CD (AUC = 0.93 and AUC = 0.95 for OTU and genus features, respectively) followed by MS, RA, and UC. Gemmiger and Faecalicoccus were identified as important features for classification of subjects to CD and HC. In general, features identified by differential abundance testing were consistent with machine learning feature importance. CONCLUSIONS: This study identified several gut microbial taxa with differential abundance patterns common to IMIDs. We also found differentially abundant taxa between IMIDs. These taxa may serve as biomarkers for the detection and diagnosis of IMIDs and suggest there may be a common component to IMID etiology.

Highlighting Clinical Metagenomics for Enhanced Diagnostic Decision-making: A Step Towards Wider Implementation.

Clinical metagenomics (CMg) is the discipline that refers to the sequencing of all nucleic acid material present within a clinical specimen with the intent to recover clinically relevant microbial information. From a diagnostic perspective, next-generation sequencing (NGS) offers the ability to rapidly identify putative pathogens and predict their antimicrobial resistance profiles to optimize targeted treatment regimens. Since the introduction of metagenomics nearly a decade ago, numerous reports have described successful applications in an increasing variety of biological specimens, such as respiratory secretions, cerebrospinal fluid, stool, blood and tissue. Considerable advancements in sequencing and computational technologies in recent years have made CMg a promising tool in clinical microbiology laboratories. Moreover, costs per sample and turnaround time from specimen receipt to clinical management continue to decrease, making the prospect of CMg more feasible. Many difficulties, however, are associated with CMg and warrant further improvements such as the informatics infrastructure and analytical pipelines. Thus, the current review focuses on comprehensively assessing applications of CMg for diagnostic and subtyping purposes.

Whole genome sequencing and phylogenetic analysis of strains of the agent of Lyme disease Borrelia burgdorferi from Canadian emergence zones.

Lyme disease is emerging in southern Canada due to range expansion of the tick vector, followed by invasion of the agent of Lyme disease Borrelia burgdorferi sensu stricto. Strain diversity, as determined by Multi Locus Sequence Typing, occurs in this zone of emergence, and this may have its origins in adaptation to ecological niches, and have phenotypic consequences for pathogenicity and serological test performance. Sixty-four unique strains were cultured from ticks collected in southern Canada and the genomes sequenced using the Illumina MiSeq platform. A maximum likelihood phylogenetic tree of the chromosome revealed two large clades with multiple subclades. Consistent with previous studies on this species, the clades were not geographically defined, and some Canadian strains were highly divergent from previously sequenced US strains. There was evidence for recombination in the chromosome but this did not affect the phylogeny. Analysis of chromosomal genes indicated that these are under intense purifying selection. Phylogenies of the accessory genome and chromosome were congruent. Therefore strain differences identified in the phylogeny of chromosomal genes likely act as a proxy for genetic determinants of phenotypic differences amongst strains that are harboured in the accessory genome. Further studies on health implications of strain diversity are needed.

A Fungal World: Could the Gut Mycobiome Be Involved in Neurological Disease?

The human microbiome has received decades of attention from scientific and medical research communities. The human gastrointestinal tract is host to immense populations of microorganisms including bacteria, viruses, archaea, and fungi (the gut microbiota). High-throughput sequencing and computational advancements provide unprecedented ability to investigate the structure and function of microbial communities associated with the human body in health and disease. Most research to date has largely focused on elucidating the bacterial component of the human gut microbiota. Study of the gut "mycobiota," which refers to the diverse array of fungal species, is a relatively new and rapidly progressing field. Though omnipresent, the number and abundance of fungi occupying the human gut is orders of magnitude smaller than that of bacteria. Recent insights however, have suggested that the gut mycobiota may be intricately linked to health and disease. Evaluation of the gut mycobiota has shown that not only are the fungal communities altered in disease, but they also play a role in maintaining intestinal homeostasis and influencing systemic immunity. In addition, it is now widely accepted that host-fungi and bacteria-fungi associations are critical to host health. While research of the gut mycobiota in health and disease is on the rise, little research has been performed in the context of neuroimmune and neurodegenerative conditions. Gut microbiota dysbiosis (specifically bacteria and archaea) have been reported in neurological diseases such as multiple sclerosis, amyotrophic lateral sclerosis, and Alzheimer's, among others. Given the widely accepted bacteria-fungi associations and paucity of mycobiota-specific studies in neurological disease, this review discusses the potential role fungi may play in multiple sclerosis and other neurological diseases. Herein, we provide an overview of recent advances in gut mycobiome research and discuss the plausible role of both intestinal and non-intestinal fungi in the context of neuroimmune and neurodegenerative conditions.

SNVPhyl: a single nucleotide variant phylogenomics pipeline for microbial genomic epidemiology.

The recent widespread application of whole-genome sequencing (WGS) for microbial disease investigations has spurred the development of new bioinformatics tools, including a notable proliferation of phylogenomics pipelines designed for infectious disease surveillance and outbreak investigation. Transitioning the use of WGS data out of the research laboratory and into the front lines of surveillance and outbreak response requires user-friendly, reproducible and scalable pipelines that have been well validated. Single Nucleotide Variant Phylogenomics (SNVPhyl) is a bioinformatics pipeline for identifying high-quality single-nucleotide variants (SNVs) and constructing a whole-genome phylogeny from a collection of WGS reads and a reference genome. Individual pipeline components are integrated into the Galaxy bioinformatics framework, enabling data analysis in a user-friendly, reproducible and scalable environment. We show that SNVPhyl can detect SNVs with high sensitivity and specificity, and identify and remove regions of high SNV density (indicative of recombination). SNVPhyl is able to correctly distinguish outbreak from non-outbreak isolates across a range of variant-calling settings, sequencing-coverage thresholds or in the presence of contamination. SNVPhyl is available as a Galaxy workflow, Docker and virtual machine images, and a Unix-based command-line application. SNVPhyl is released under the Apache 2.0 license and available at http://snvphyl.readthedocs.io/ or at https://github.com/phac-nml/snvphyl-galaxy.

Neptune: a bioinformatics tool for rapid discovery of genomic variation in bacterial populations.

The ready availability of vast amounts of genomic sequence data has created the need to rethink comparative genomics algorithms using 'big data' approaches. Neptune is an efficient system for rapidly locating differentially abundant genomic content in bacterial populations using an exact k-mer matching strategy, while accommodating k-mer mismatches. Neptune's loci discovery process identifies sequences that are sufficiently common to a group of target sequences and sufficiently absent from non-targets using probabilistic models. Neptune uses parallel computing to efficiently identify and extract these loci from draft genome assemblies without requiring multiple sequence alignments or other computationally expensive comparative sequence analyses. Tests on simulated and real datasets showed that Neptune rapidly identifies regions that are both sensitive and specific. We demonstrate that this system can identify trait-specific loci from different bacterial lineages. Neptune is broadly applicable for comparative bacterial analyses, yet will particularly benefit pathogenomic applications, owing to efficient and sensitive discovery of differentially abundant genomic loci. The software is available for download at: http://github.com/phac-nml/neptune.

Metagenomics: The Next Culture-Independent Game Changer.

A trend towards the abandonment of obtaining pure culture isolates in frontline laboratories is at a crossroads with the ability of public health agencies to perform their basic mandate of foodborne disease surveillance and response. The implementation of culture-independent diagnostic tests (CIDTs) including nucleic acid and antigen-based assays for acute gastroenteritis is leaving public health agencies without laboratory evidence to link clinical cases to each other and to food or environmental substances. This limits the efficacy of public health epidemiology and surveillance as well as outbreak detection and investigation. Foodborne outbreaks have the potential to remain undetected or have insufficient evidence to support source attribution and may inadvertently increase the incidence of foodborne diseases. Next-generation sequencing of pure culture isolates in clinical microbiology laboratories has the potential to revolutionize the fields of food safety and public health. Metagenomics and other 'omics' disciplines could provide the solution to a cultureless future in clinical microbiology, food safety and public health. Data mining of information obtained from metagenomics assays can be particularly useful for the identification of clinical causative agents or foodborne contamination, detection of AMR and/or virulence factors, in addition to providing high-resolution subtyping data. Thus, metagenomics assays may provide a universal test for clinical diagnostics, foodborne pathogen detection, subtyping and investigation. This information has the potential to reform the field of enteric disease diagnostics and surveillance and also infectious diseases as a whole. The aim of this review will be to present the current state of CIDTs in diagnostic and public health laboratories as they relate to foodborne illness and food safety. Moreover, we will also discuss the diagnostic and subtyping utility and concomitant bias limitations of metagenomics and comparable detection techniques in clinical microbiology, food and public health laboratories. Early advances in the discipline of metagenomics, however, have indicated noteworthy challenges. Through forthcoming improvements in sequencing technology and analytical pipelines among others, we anticipate that within the next decade, detection and characterization of pathogens via metagenomics-based workflows will be implemented in routine usage in diagnostic and public health laboratories.

A Study of the Infant Nasal Microbiome Development over the First Year of Life and in Relation to Their Primary Adult Caregivers Using cpn60 Universal Target (UT) as a Phylogenetic Marker.

Whereas the infant gut microbiome is the subject of intense study, relatively little is known regarding the nares microbiome in newborns and during early life. This study aimed to survey the typical composition and diversity of human anterior nare microflora for developing infants over time, and to explore how these correlate to their primary caregivers. Single nare swabs were collected at five time points over a one-year period for each subject from infant-caregiver pairs. Our study comprised of 50 infants (recruited at 2 weeks, post delivery) and their 50 primary caregivers. Applying the chaperonin-60 (cpn60) universal target (UT) amplicon as our molecular barcoding marker to census survey the microbial communities, we longitudinally surveyed infant nares microbiota at 5 time points over the course of the first year of life. The inter- and intra-subject diversity was catalogued and compared, both longitudinally and relative to their adult primary caregivers. Although within-subject variability over time and inter-subject variability were both observed, the assessment detected only one or two predominant genera for individual infant samples, belonging mainly to phyla Actinobacteria, Firmicutes, and Proteobacteria. Consistent with previously observed microbial population dynamics in other body sites, the diversity of nares microflora increased over the first year of life and infants showed differential operational taxonomic units (OTUs) relative to their matched primary caregiver. The collected evidence also support that both temporal and seasonal changes occur with respect to carriage of potentially pathogenic bacteria (PPBs), which may influence host predisposition to infection. This pilot study surveying paired infant/caregiver nare microbiomes provides novel longitudinal diversity information that is pertinent to better understanding nare microbiome development in infants.

Comparison of Sample Preparation Methods Used for the Next-Generation Sequencing of Mycobacterium tuberculosis.

The advent and widespread application of next-generation sequencing (NGS) technologies to the study of microbial genomes has led to a substantial increase in the number of studies in which whole genome sequencing (WGS) is applied to the analysis of microbial genomic epidemiology. However, microorganisms such as Mycobacterium tuberculosis (MTB) present unique problems for sequencing and downstream analysis based on their unique physiology and the composition of their genomes. In this study, we compare the quality of sequence data generated using the Nextera and TruSeq isolate preparation kits for library construction prior to Illumina sequencing-by-synthesis. Our results confirm that MTB NGS data quality is highly dependent on the purity of the DNA sample submitted for sequencing and its guanine-cytosine content (or GC-content). Our data additionally demonstrate that the choice of library preparation method plays an important role in mitigating downstream sequencing quality issues. Importantly for MTB, the Illumina TruSeq library preparation kit produces more uniform data quality than the Nextera XT method, regardless of the quality of the input DNA. Furthermore, specific genomic sequence motifs are commonly missed by the Nextera XT method, as are regions of especially high GC-content relative to the rest of the MTB genome. As coverage bias is highly undesirable, this study illustrates the importance of appropriate protocol selection when performing NGS studies in order to ensure that sound inferences can be made regarding mycobacterial genomes.