The soil microbiomes of forest ecosystems in Kenya: their diversity and environmental drivers.

Soil microbiomes in forest ecosystems act as both nutrient sources and sinks through a range of processes including organic matter decomposition, nutrient cycling, and humic compound incorporation into the soil. Most forest soil microbial diversity studies have been performed in the northern hemisphere, and very little has been done in forests within African continent. This study examined the composition, diversity and distribution of prokaryotes in Kenyan forests top soils using amplicon sequencing of V4-V5 hypervariable region of the 16S rRNA gene. Additionally, soil physicochemical characteristics were measured to identify abiotic drivers of prokaryotic distribution. Different forest soils were found to have statistically distinct microbiome compositions, with Proteobacteria and Crenarchaeota taxa being the most differentially abundant across regions within bacterial and archaeal phyla, respectively. Key bacterial community drivers included pH, Ca, K, Fe, and total N while archaeal diversity was shaped by Na, pH, Ca, total P and total N. To contextualize the prokaryote diversity of Kenyan forest soils on a global scale, the sample set was compared to amplicon data obtained from forest biomes across the globe; displaying them to harbor distinct microbiomes with an over-representation of uncultured taxa such as TK-10 and Ellin6067 genera.

Delineation of a T-cell receptor CDR3-cancer mutanome aromaticity factor, assessable via blood samples, that facilitates the establishment of survival distinctions in bladder cancer.

PURPOSE: A very large and still expanding collection of adaptive immune receptor (IR) recombination reads, representing many diseases, is becoming available for downstream analyses. Among the most productive approaches has been to establish risk stratification parameters via the chemical features of the IR complementarity determining region-3 (CDR3) amino acid (AA) sequences, particularly for large datasets where clinical information is available. Because the IR CDR3 AA sequences often play a large role in antigen binding, the chemistry of these AAs has the likelihood of representing a disease-related fingerprint as well as providing pre-screening information for candidate antigens. To approach this issue in a novel manner, we developed a bladder cancer, case evaluation approach based on CDR3 aromaticity. METHODS: We developed and applied a simple and efficient algorithm for assessing aromatic, chemical complementarity between T-cell receptor (TCR) CDR3 AA sequences and the cancer specimen mutanome. RESULTS: Results indicated a survival distinction for aromatic CDR3-aromatic mutanome complementary, versus non-complementary, bladder cancer case sets. This result applied to both tumor resident and blood TCR CDR3 AA sequences and was supported by CDR3 AA sequences represented by both exome and RNAseq files. CONCLUSION: The described aromaticity factor algorithm has the potential of assisting in prognostic assessments and guiding immunotherapies for bladder cancer.