Pathogenesis of visna. III. Immune responses to central nervous system antigens in experimental allergic encephalomyelitis and visna.

Experimental allergic encephalomyelitis (EAE) was induced in sheep in pursuit of the hypothesis that an immune response against central nervous system antigens might play a role in the pathogenesis of visna. Nine to 12 days after sensitization with whole sheep brain and complete Freund's adjuvant, approximately 50% of sheep developed a fulminating lethal form of EAE. Following a second sensitization, another 20% of animals developed EAE whereas a residual 30% failed to develop any signs or histologic evidence of disease. A histologic comparison of EAE and visna indicated considerable similarity in the nature of the pathologic process. However, the distribution of lesions was quite different, suggesting cellular responses to two different antigens, Cell-mediated immunity to myelin basic protein, as measured by lymphocyte blast transformation, was minimally elevated in sheep sensitized with whole brain suspension in complete Freund's adjuvant, whereas no response could be detected in visna-infected sheep. Complement-fixing antibody titers to basic protein and to a lipid antigen of brain, probably galactocerebroside, rose briskly after sensitization. In visna-infected sheep, on the other hand, there was no increase in either antibody. A large proportion of both Hampshire and Icelandic sheep had low levels of complement-fixing antibody to central nervous system antigens prior to induction of EAE or infection with visna virus. The origin of this antibody is undetermined, but it appeared to have no effect on the course of either disease. Immunosuppression of sheep with antilymphoid serum prevented induction of EAE. Acute EAE was, thus, successfully induced in sheep and used as a model to measure immune responses to central nervous system antigens and as an index of immunosuppression. However, these comparative studies did not provide any evidence for the role of an autoimmune response, to the two central nervous system antigens tested, in the pathogenesis of visna.     

Pathogenesis of visna. II. Effect of immunosuppression upon early central nervous system lesions.

It was hypothesized that the lesions of visna might represent an immunopathologic process. To test this hypothesis, a 1-month schedule of immunosuppressive treatment was devised, using horse anti-sheep thymocyte serum. In Hampshire sheep, this regime was shown to protect against experimental allergic encephalomyelitis, to inhibit development of tuberculin hypersensitivity, to retard rejection of skin homografts by 3 weeks, and to markedly reduce the number and mitogenic responsiveness of peripheral blood lymphocytes. Two groups of Icelandic sheep received intracerebral inoculations of visna virus, and one group was treated with horse antisheep thymocyte serum supplemented by a short terminal course of cyclophosphamide. Central nervous system lesions were seen in only one of eight suppressed animals at sacrifice 25 days after infection, whereas definite lesions were present in eight of eight infected control animals. The frequency of central nervous system virus isolation was similar in the two groups, indicating that treatment suppressed the cellular proliferative response without preventing the central nervous system phase of infection. Sheep receiving horse antisheep thymocyte serum had a reduced number of virus isolations from peripheral lymphoid tissue, presumably reflecting the lympholytic effect of treatment. These observations are consistent with the immunopathologic hypothesis and suggest several different ways in which suppression could modify the immune response to visna virus.     

Systems biology approach to functionally assess the Clostridioides difficile pangenome reveals genetic diversity with discriminatory power

Combatting Clostridioides difficile infections, a dominant cause of hospital-associated infections with incidence and resulting deaths increasing worldwide, is complicated by the frequent emergence of new virulent strains. Here, we employ whole-genome sequencing, high-throughput phenotypic screenings, and genome-scale models of metabolism to evaluate the genetic diversity of 451 strains of C. difficile. Constructing the C. difficile pangenome based on this set revealed 9,924 distinct gene clusters, of which 2,899 (29%) are defined as core, 2,968 (30%) are defined as unique, and the remaining 4,057 (41%) are defined as accessory. We develop a strain typing method, sequence typing by accessory genome (STAG), that identifies 176 genetically distinct groups of strains and allows for explicit interrogation of accessory gene content. Thirty-five strains representative of the overall set were experimentally profiled on 95 different nutrient sources, revealing 26 distinct growth profiles and unique nutrient preferences; 451 strain-specific genome scale models of metabolism were constructed, allowing us to computationally probe phenotypic diversity in 28,864 unique conditions. The models create a mechanistic link between the observed phenotypes and strain-specific genetic differences and exhibit an ability to correctly predict growth in 76% of measured cases. The typing and model predictions are used to identify and contextualize discriminating genetic features and phenotypes that may contribute to the emergence of new problematic strains.

The bacterial pathogen Clostridioides difficile remains the most common health care–associated infection with an ever-evolving and complex epidemiology. C. difficile is recognized as an urgent threat by the Centers for Disease Control and Prevention (CDC) and has been conservatively estimated at over 220,000 cases in hospitalized patients and nearly 13,000 deaths within the United States annually (1). The disruption of natural colonic microbiota following antibiotic use is the leading risk factor for C. difficile infection (CDI), and recurrent infections occur in ∼35% of patients (2–4). Two toxins, TcdA and TcdB, are the primary virulence factors for symptomatic infection (5). However, virulence is also attributed by other factors, including the cytolethal distending toxin, sporulation, flagella, and adhesins (6–12). Overall, the plasticity of the C. difficile genome has contributed to divergent lineages distinguished by evolutionarily advantageous genetic traits that result in increased antimicrobial resistance, virulence, and metabolic capabilities for survival within the gut (13, 14). The bevy of accessory gene content present across strains in this species has complicated attempts to contextualize strain relationships among this complex population.Molecular typing techniques that evaluate strain relatedness have been used to evaluate C. difficile epidemiology and track transmission of virulent lineages. The C. difficile genome has sufficient intraspecies diversity within the intergenic spacer regions of ribosomal RNA (rRNA) genes for the successful use and adoption of PCR ribotyping, the primary molecular typing method for C. difficile (15–18). As a result, the most prevalent and hypervirulent C. difficile strains globally have been dubbed ribotype (RT) 027 (RT027) and RT078 (12, 19, 20). Additionally, multilocus sequence typing (MLST) is widely used in population studies as a means of distinguishing strains through the allelic profile of designated housekeeping genes (21–23). In addition to these two techniques, there are several other typing methods, including multilocus variable-number tandem repeat analysis, pulsed-field gel electrophoresis, restriction endonuclease analysis, toxinotyping, and surface-layer protein A–encoding gene typing. Each of these methods has unique levels of discriminatory power as well as unique limitations (24). While these typing schemes have proven useful in understanding CDI epidemiology, the most widely adopted schemes (PCR ribotyping and MLST) lack the resolution to distinguish more closely related strains. To obtain mechanistic insight into outbreaks, whole-genome sequencing (WGS) methods need to be employed.Advancements in sequencing technologies have resulted in an explosion in the availability of quality WGS data (25) promising new and comprehensive approaches to strain typing (26–28). In this age of high-throughput sequencing, comparative genomics analysis has been largely stratified into two approaches: single-nucleotide variants and gene by gene comparisons. In the latter case for C. difficile, core-genome multilocus sequence typing (cgMLST) and whole-genome MLST extensions of classical MLST have been developed (29, 30). While these techniques have increased the resolution of typing approaches, key connections between the genomic diversity driving strain types and resulting diversity of phenotypes have remained elusive. A deeper understanding of the functional diversity across this species is needed and must be rooted to the enormous genetic diversity observed.In recent years, systems biology tools have been challenged with extracting knowledge from the enormous amount of omics data available. In particular, the substantial variability in genomic content and function across strains of a species can be analyzed efficiently through a combination of comparative genomics and various modeling frameworks (31–33). Strain-specific genetic variation can be usefully organized through a pangenomic perspective that delineates and organizes a species’ gene portfolio (34, 35). Additionally, genome-scale models (GEMs) of metabolism have served as tools to mechanistically link genotype to phenotype particularly in terms of growth capabilities. Computation of catabolic capabilities based on genome sequences has provided additional insight into metabolic variability and association to lifestyle niche (36, 37). To increase understanding of the diversity exhibited by C. difficile, we have executed a holistic systems biology analysis encompassing both a functional genomics assessment of the pangenome and an in-depth analysis of experimental growth phenotypes aided by construction and use of GEMs. Moreover, we developed a strain typing method based on the accessory gene content, sequence typing by accessory genome (STAG), that allows for explicit investigation into the gene clusters driving the separation of strain groups. This method expands the tool kit for analysis of WGS strain typing across a broad array of disciplines.     

Characterization of novel Mycobacterium tuberculosis pncA gene mutations in clinical isolates from the Ukraine

Multidrug-resistant (MDR) and extensively drug-resistant (XDR) Mycobacterium tuberculosis cases in the Ukraine are increasing. Pyrazinamide (PZA) is critically important for first- and second-line tuberculosis (TB) treatment regimes. However, PZA drug susceptibility testing is time consuming and technically challenging. The present study utilized Next-generation sequencing (NGS) to identify mutations in the pncA gene from clinical isolates and to assess the prevalence of pncA gene mutations in MDR/XDR-TB patients. Clinical isolates were inactivated in molecular transport media and shipped from Kharkiv, Ukraine, to San Antonio, TX. Whole-genome and targeted pncA gene sequencing was carried out using Illumina MiSeq instrumentation. Mutations were noted in 67 of 91 (74%) clinical isolates comprising substitutions, insertions, and deletions in the pncA coding and upstream promoter region. Of 45 mutation types, there were 11 novel, i.e., to date unknown, pncA mutations identified of which 3 were confirmed PZA resistant. Seven isolates contained mixed base mutations, whereas 4 harbored doubled mutations. Data reported here further support use of NGS for pncA gene characterization and may contribute in significant fashion to PZA therapy, especially in MDR- and XDR-TB patients.     

Global reconstruction of the human metabolic network based on genomic and bibliomic data

Metabolism is a vital cellular process, and its malfunction is a major contributor to human disease. Metabolic networks are complex and highly interconnected, and thus systems-level computational approaches are required to elucidate and understand metabolic genotype-phenotype relationships. We have manually reconstructed the global human metabolic network based on Build 35 of the genome annotation and a comprehensive evaluation of >50 years of legacy data (i.e., bibliomic data). Herein we describe the reconstruction process and demonstrate how the resulting genome-scale (or global) network can be used (i) for the discovery of missing information, (ii) for the formulation of an in silico model, and (iii) as a structured context for analyzing high-throughput biological data sets. Our comprehensive evaluation of the literature revealed many gaps in the current understanding of human metabolism that require future experimental investigation. Mathematical analysis of network structure elucidated the implications of intracellular compartmentalization and the potential use of correlated reaction sets for alternative drug target identification. Integrated analysis of high-throughput data sets within the context of the reconstruction enabled a global assessment of functional metabolic states. These results highlight some of the applications enabled by the reconstructed human metabolic network. The establishment of this network represents an important step toward genome-scale human systems biology.