microshades: An R Package for Improving Color Accessibility and Organization of Microbiome Data.

When creating figures, it is important to consider that individuals with color vision deficiency (CVD) may not perceive all colors. While there are several CVD-friendly color palettes, they are often insufficient for working with microbiome data. Here, we introduce microshades, an R package for creating CVD-accessible microbiome figures.

Network-Based Differences in the Vaginal and Bladder Microbial Communities Between Women With and Without Urgency Urinary Incontinence.

Background: Little is known about the relationship of proximal urogenital microbiomes in the bladder and the vagina and how this contributes to bladder health. In this study, we use a microbial ecology and network framework to understand the dynamics of interactions/co-occurrences of bacteria in the bladder and vagina in women with and without urgency urinary incontinence (UUI). Methods: We collected vaginal swabs and catheterized urine specimens from 20 women with UUI (cases) and 30 women without UUI (controls). We sequenced the V4 region of the bacterial 16S rRNA gene and evaluated using alpha and beta diversity metrics. We used microbial network analysis to detect interactions in the microbiome and the betweenness centrality measure to identify central bacteria in the microbial network. Bacteria exhibiting maximum betweenness centrality are considered central to the microbe-wide networks and likely maintain the overall microbial network structure. Results: There were no significant differences in the vaginal or bladder microbiomes between cases and controls using alpha and beta diversity. Silhouette metric analysis identified two distinct microbiome clusters in both the bladder and vagina. One cluster was dominated by Lactobacillus genus while the other was more diverse. Network-based analyses demonstrated that vaginal and bladder microbial networks were different between cases and controls. In the vagina, there were similar numbers of genera and subgroup clusters in each network for cases and controls. However, cases tend to have more unique bacterial co-occurrences. While Bacteroides and Lactobacillus were the central bacteria with the highest betweenness centrality in controls, Aerococcus had the highest centrality in cases and correlated with bacteria commonly associated with bacterial vaginosis. In the bladder, cases have less than half as many network clusters compared to controls. Lactobacillus was the central bacteria in both groups but associated with several known uropathogens in cases. The number of shared bacterial genera between the bladder and the vagina differed between cases and controls, with cases having larger overlap (43%) compared to controls (29%). Conclusion: Our study shows overlaps in microbial communities of bladder and vagina, with higher overlap in cases. We also identified differences in the bacteria that are central to the overall community structure.

Rapid and simultaneous detection of Mycobacterium tuberculosis complex and Beijing/W genotype in sputum by an optimized DNA extraction protocol and a novel multiplex real-time PCR.

Rapid diagnosis and genotyping of Mycobacterium tuberculosis by molecular methods are often limited by the amount and purity of DNA extracted from body fluids. In this study, we evaluated 12 DNA extraction methods and developed a highly sensitive protocol for mycobacterial DNA extraction directly from sputa using surface-coated magnetic particles. We have also developed a novel multiplex real-time PCR for simultaneous identification of M. tuberculosis complex and the Beijing/W genotype (a hypervirulent sublineage of M. tuberculosis) by using multiple fluorogenic probes targeting both the M. tuberculosis IS6110 and the Rv0927c-pstS3 intergenic region. With reference strains and clinical isolates, our real-time PCR accurately identified 20 non-Beijing/W and 20 Beijing/W M. tuberculosis strains from 17 different species of nontuberculosis Mycobacterium (NTM). Further assessment of our DNA extraction protocol and real-time PCR with 335 nonduplicate sputum specimens correctly identified all 74 M. tuberculosis culture-positive specimens. In addition, 15 culture-negative specimens from patients with confirmed tuberculosis were also identified. No cross-reactivity was detected with NTM specimens (n = 31). The detection limit of the assay is 10 M. tuberculosis bacilli, as determined by endpoint dilution analysis. In conclusion, an optimized DNA extraction protocol coupled with a novel multiprobe multiplex real-time PCR for the direct detection of M. tuberculosis, including Beijing/W M. tuberculosis, was found to confer high sensitivity and specificity. The combined procedure has the potential to compensate for the drawbacks of conventional mycobacterial culture in routine clinical laboratory setting, such as the lengthy incubation period and the limitation to viable organisms.

Modelling disease risk for amyloid A (AA) amyloidosis in non-human primates using machine learning.

Objective: Amyloid A (AA) amyloidosis is found in humans and non-human primates, but quantifying disease risk prior to clinical symptoms is challenging. We applied machine learning to identify the best predictors of amyloidosis in rhesus macaques from available clinical and pathology records. To explore potential biomarkers, we also assessed whether changes in circulating serum amyloid A (SAA) or lipoprotein profiles accompany the disease. Methods: We conducted a retrospective study using 86 cases and 163 controls matched for age and sex. We performed data reduction on 62 clinical, pathological and demographic variables, and applied multivariate modelling and model selection with cross-validation. To test the performance of our final model, we applied it to a replication cohort of 2,775 macaques. Results: The strongest predictors of disease were colitis, gastrointestinal adenocarcinoma, endometriosis, arthritis, trauma, diarrhoea and number of pregnancies. Sensitivity and specificity of the risk model were predicted to be 82%, and were assessed at 79 and 72%, respectively. Total, low density lipoprotein and high density lipoprotein cholesterol levels were significantly lower, and SAA levels and triglyceride-to-HDL ratios were significantly higher in cases versus controls. Conclusion: Machine learning is a powerful approach to identifying macaques at risk of AA amyloidosis, which is accompanied by increased circulating SAA and altered lipoprotein profiles.

Unraveling methylation changes of host macrophages in Mycobacterium tuberculosis infection.

OBJECTIVES: To characterize at high resolution DNA methylation changes of cytokines which occur in the genome of macrophages in association with Mycobacterium tuberculosis (MTB) infection METHODS: We studied the methylation profiles of THP-1 derived macrophage cells infected with clinical MTB strains [Beijing/W & non-Beijing/W lineage, sensitive (INH(S), RIF(S)) & resistant (INH(R), RIF(R)) strains] and of host macrophages from MTB infected cohorts (active & latent patients) with the human methylation CpG islands microarrays. RESULTS: Methylated modification on the promoter sequences of cytokines and their receptors were found to be associated with MTB infection in a strain- and host-dependent manner. Our epigenetic analyses revealed that infection with Beijing/W MTB strains enhanced IL6R, IL4R and IL17R hyper-methylations in infected macrophages. Validation of IL6R methylated sequence confirmed that MTB infection induced DNA methylation of CpG67 region in the IL6R promoter. In addition, studies on the human macrophage methylation profiles from the patient cohorts indicated that the methylation rate of IL17 family members and related genes were significantly altered in patients with active MTB infections. CONCLUSIONS: Our study offered novel insights into the epigenetic changes in the interaction of host macrophages in MTB infections and warrant further explorations into these changes in modulating the immune response in active and latent MTB infections.

Rapid quantification of hepatitis B virus DNA by real-time PCR using fluorescent hybridization probes.

A highly sensitive and rapid assay has been developed to quantify hepatitis B virus (HBV) DNA, based on the fluorescence resonance energy transfer principle and real-time PCR, using the LightCycler and a pair of specific fluorescent hybridization probes. This LightCycler real-time PCR assay (LC-PCR) detected HBV DNA in a linear range from 10(1) to 10(8) copies per reaction (250-2.5 x 10(9) copies ml(-1)), with a rapid PCR cycling time of 35 min. The assay was validated with two EUROHEP HBV DNA standards (ad and ay subtypes) and exhibited low intra-assay (< 6 %) and inter-assay (< 16 %) variation for both subtypes over the complete range of 7 orders of magnitude. The assay was evaluated clinically using serum samples from 120 HBsAg(+) individuals and 45 healthy controls who were negative for both HBsAg and anti-HBc. Levels of HBV DNA were measured in these samples using both the LC-PCR and Digene Hybrid Capture II HBV DNA (HCII) assays. The prevalence rates for HBV DNA in the HBsAg(+) serum samples were respectively 95 % (114/120) and 56 % (67/120) by LC-PCR and HCII (P < 0.01). All 67 HCII-positive samples tested positive with LC-PCR, while the 47 discordant samples showed low levels of HBV DNA (down to 265 copies ml(-1)), detectable only by the more sensitive LC-PCR assay. Levels of HBV DNA as measured by the two assays showed good correlation (r = 0.902; P < 0.001). The level of HBV DNA was significantly higher in HBeAg(+) than anti-HBe(+) samples (median 1.5 x 10(7) vs 4.6 x 10(4) copies ml(-1); P < 0.01). It is concluded that this LC-PCR assay is clinically useful for the rapid, sensitive and accurate measurement of HBV DNA.

Effect of CKBM on prostate cancer cell growth in vitro and in vivo.

Prostate carcinoma and metastasis are common among male subjects worldwide. CKBM is a drug product targeting prostate cancer in multiple ways. Prostate cancer cell lines PC3 and DU145 were treated with CKBM. The effect of CKBM on the cell's viability, cell cycle, adhesive and invasive properties and its growth in an animal model were assessed. Results indicated that CKBM inhibited PC3 and DU145 cell growth in vitro at IC(50 )values 3.923 and 4.697% respectively, and it brought about cell cycle arrest at G2/M phase. CKBM also attenuated DU145 cells to invade and adhere to extracellular matrices including Matrigel, laminin, fibronectin and collagen IV. Moreover, PC3 tumor xenograft growth was inhibited by over 60% after 28-day of 0.2, 0.4 or 0.8 ml/day CKBM treatment. The present study indicates that CKBM is effective against prostate cancer cell growth in vitro and in vivo. Further studies are required to elucidate its mechanism of action.