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BackgroundGenomics-driven discoveries of microbial species have provided extraordinary insights into the biodiversity of human microbiota. In addition, a significant portion of genetic variation between microbiota exists at the subspecies, or strain, level. High-resolution genomics to investigate species- and strain-level diversity and mechanistic studies, however, rely on the availability of individual microbes from a complex microbial consortia. High-throughput approaches are needed to acquire and identify the significant species- and strain-level diversity present in the oral, skin, and gut microbiome. Here, we describe and validate a streamlined workflow for cultivating dominant bacterial species and strains from the skin, oral, and gut microbiota, informed by metagenomic sequencing, mass spectrometry, and strain profiling.ResultsOf total genera discovered by either metagenomic sequencing or culturomics, our cultivation pipeline recovered between 18.1–44.4% of total genera identified. These represented a high proportion of the community composition reconstructed with metagenomic sequencing, ranging from 66.2–95.8% of the relative abundance of the overall community. Fourier-Transform Infrared spectroscopy (FT-IR) was effective in differentiating genetically distinct strains compared with whole-genome sequencing, but was less effective as a proxy for genetic distance.ConclusionsUse of a streamlined set of conditions selected for cultivation of skin, oral, and gut microbiota facilitates recovery of dominant microbes and their strain variants from a relatively large sample set. FT-IR spectroscopy allows rapid differentiation of strain variants, but these differences are limited in recapitulating genetic distance. Our data highlights the strength of our cultivation and characterization pipeline, which is in throughput, comparisons with high-resolution genomic data, and rapid identification of strain variation.

Background Lightheadedness, fatigue, weakness, heart palpitations, cognitive dysfunction, muscle pain, and exercise intolerance are some of the symptoms of orthostatic intolerance (OI). There is substantial comorbidity of OI in ME/CFS (Myalgic Encephalomyelitis/Chronic Fatigue Syndrome). The 10-minute NASA Lean Test (NLT) is a simple, point-of-care method that can aid ME/CFS diagnosis and guide management and treatment of OI. The objective of this study was to understand the hemodynamic changes that occur in ME/CFS patients during the 10-minute NLT. Methods A total of 150 ME/CFS patients and 75 age, gender and race matched healthy controls (HCs) were enrolled. We recruited 75 ME/CFS patients who had been sick for less than 4 years ( 10 ME/CFS). The 10-minute NLT involves measurement of blood pressure and heart rate while resting supine and every minute for 10 min while standing with shoulder-blades on the wall for a relaxed stance. Spontaneously reported symptoms are recorded during the test. ANOVA and regression analysis were used to test for differences and relationships in hemodynamics, symptoms and upright activity between groups. Results At least 5 min of the 10-minute NLT were required to detect hemodynamic changes. The 10 ME/CFS and HCs. The 10 ME/CFS and HCs. The circulatory decompensation observed in the Conclusions Circulatory decompensation characterized by increased heart rate and abnormally narrow pulse pressure was identified in a subgroup of ME/CFS patients who have been sick for 10 ME/CFS group had less pronounced hemodynamic changes during the NLT possibly from adaptation and compensation that occurs over time. The 10-minute NLT is a simple and clinically useful point-of-care method that can be used for early diagnosis of ME/CFS and help guide OI treatment.

Background Chronic Fatigue Syndrome (CFS) came to attention in the 1980s, but initial investigations did not find organic causes. Now decades later, the etiology of CFS has yet to be understood, and the role of genetic predisposition in CFS remains controversial. Recent reports of CFS association with the retrovirus xenotropic murine leukemic virus-related virus (XMRV) or other murine leukemia related retroviruses (MLV) might also suggest underlying genetic implications within the host immune system. Methods We present analyses of familial clustering of CFS in a computerized genealogical resource linking multiple generations of genealogy data with medical diagnosis data of a large Utah health care system. We compare pair-wise relatedness among cases to expected relatedness in the Utah population, and we estimate risk for CFS for first, second, and third degree relatives of CFS cases. Results We observed significant excess relatedness of CFS cases compared to that expected in this population. Significant excess relatedness was observed for both close (p Conclusions These analyses provide strong support for a heritable contribution to predisposition to Chronic Fatigue Syndrome. A population of high-risk CFS pedigrees has been identified, the study of which may provide additional understanding.