Microbial diversity and function in crystalline basement beneath the Deccan Traps explored in a 3 km borehole at Koyna,western India

Deep terrestrial subsurface represents a huge repository of global prokaryotic biomass. Given its vastness and importance, microbial life within the deep subsurface continental crust remains under-represented in global studies. We characterize the microbial communities of deep, extreme and oligotrophic realm hosted by crystalline Archaean granitic rocks underneath the Deccan Traps, through sampling via 3000 m deep scientific borehole at Koyna, India through metagenomics, amplicon sequencing and cultivation-based analyses. Gene sequences 16S rRNA (7.37 × 10⁶) show considerable bacterial diversity and the existence of a core microbiome (5724 operational taxonomic units conserved out of a total 118,064 OTUs) across the depths. Relative abundance of different taxa of core microbiome varies with depth in response to prevailing lithology and geochemistry. Co-occurrence network analysis and cultivation attempt to elucidate close interactions among autotrophic and organotrophic bacteria. Shotgun metagenomics reveals a major role of autotrophic carbon fixation via the Wood–Ljungdahl pathway and genes responsible for energy and carbon metabolism. Deeper analysis suggests the existence of an ‘acetate switch’, coordinating biosynthesis and cellular homeostasis. We conclude that the microbial life in the nutrient- and energy-limited deep granitic crust is constrained by the depth and managed by a few core members via a close interplay between autotrophy and organotrophy.     

In vitro plant regeneration through somatic embryogenesis in Anaphyllum wightii Schott

In Vitro Cellular & Developmental Biology - Plant - Anaphyllum wightii Schott. is an ethnomedicinally significant plant endemic to the southern region of Western Ghats. The present study aimed...     

Effects of predator type and alternative prey on mosquito egg raft predation and destruction

Hydrobiologia - Differences in habitat and diet between species are often associated with morphological differences. Habitat and trophic adaptation have therefore been proposed as important drivers...     

Biofouling effects on the performance of microbial fuel cells and recent advances in biotechnological and chemical strategies for mitigation

The occurrence of biofouling in MFC can cause severe problems such as hindering proton transfer and increasing the ohmic and charge transfer resistance of cathodes, which results in a rapid decline in performance of MFC. This is one of the main reasons why scaling-up of MFCs has not yet been successfully accomplished. The present review article is a wide-ranging attempt to provide insights to the biofouling mechanisms on surfaces of MFC, mainly on proton exchange membranes and cathodes, and their effects on performance of MFC based on theoretical and practical evidence. Various biofouling mitigation techniques for membranes are discussed, including preparation of antifouling composite membranes, modification of the physical and chemical properties of existing membranes, and coating with antifouling agents. For cathodes of MFC, use of Ag nanoparticles, Ag-based composite nanoparticles, and antifouling chemicals is outlined in considerable detail. Finally, prospective techniques for mitigation of biofouling are discussed, which have not been given much previous attention in the field of MFC research. This article will help to enhance understanding of the severity of biofouling issues in MFCs and provides up-to-date solutions. It will be beneficial for scientific communities for further strengthening MFC research and will also help in progressing this cutting-edge technology to scale-up, using the most efficient methods as described here.     

Determining clinically relevant features in cytometry data using persistent homology

Cytometry experiments yield high-dimensional point cloud data that is difficult to interpret manually. Boolean gating techniques coupled with comparisons of relative abundances of cellular subsets is the current standard for cytometry data analysis. However, this approach is unable to capture more subtle topological features hidden in data, especially if those features are further masked by data transforms or significant batch effects or donor-to-donor variations in clinical data. We present that persistent homology, a mathematical structure that summarizes the topological features, can distinguish different sources of data, such as from groups of healthy donors or patients, effectively. Analysis of publicly available cytometry data describing non-naïve CD8+ T cells in COVID-19 patients and healthy controls shows that systematic structural differences exist between single cell protein expressions in COVID-19 patients and healthy controls. We identify proteins of interest by a decision-tree based classifier, sample points randomly and compute persistence diagrams from these sampled points. The resulting persistence diagrams identify regions in cytometry datasets of varying density and identify protruded structures such as ‘elbows’. We compute Wasserstein distances between these persistence diagrams for random pairs of healthy controls and COVID-19 patients and find that systematic structural differences exist between COVID-19 patients and healthy controls in the expression data for T-bet, Eomes, and Ki-67. Further analysis shows that expression of T-bet and Eomes are significantly downregulated in COVID-19 patient non-naïve CD8+ T cells compared to healthy controls. This counter-intuitive finding may indicate that canonical effector CD8+ T cells are less prevalent in COVID-19 patients than healthy controls. This method is applicable to any cytometry dataset for discovering novel insights through topological data analysis which may be difficult to ascertain otherwise with a standard gating strategy or existing bioinformatic tools.     

Spatial patterns of microbial diversity and activity in an aged creosote-contaminated site

Restoration of polluted sites via in situ bioremediation relies heavily on the indigenous microbes and their activities. Spatial heterogeneity of microbial populations, contaminants and soil chemical parameters on such sites is a major hurdle in optimizing and implementing an appropriate bioremediation regime. We performed a grid-based sampling of an aged creosote-contaminated site followed by geostatistical modelling to illustrate the spatial patterns of microbial diversity and activity and to relate these patterns to the distribution of pollutants. Spatial distribution of bacterial groups unveiled patterns of niche differentiation regulated by patchy distribution of pollutants and an east-to-west pH gradient at the studied site. Proteobacteria clearly dominated in the hot spots of creosote pollution, whereas the abundance of Actinobacteria, TM7 and Planctomycetes was considerably reduced from the hot spots. The pH preferences of proteobacterial groups dominating in pollution could be recognized by examining the order and family-level responses. Acidobacterial classes came across as generalists in hydrocarbon pollution whose spatial distribution seemed to be regulated solely by the pH gradient. Although the community evenness decreased in the heavily polluted zones, basal respiration and fluorescein diacetate hydrolysis rates were higher, indicating the adaptation of specific indigenous microbial populations to hydrocarbon pollution. Combining the information from the kriged maps of microbial and soil chemistry data provided a comprehensive understanding of the long-term impacts of creosote pollution on the subsurface microbial communities. This study also highlighted the prospect of interpreting taxa-specific spatial patterns and applying them as indicators or proxies for monitoring polluted sites.     

Insights into plastome of Fagonia indica Burm.f. (Zygophyllaceae): organization,annotation and phylogeny

The enhanced understanding of chloroplast genomics would facilitate various biotechnology applications; however, the chloroplast (cp) genome / plastome characteristics of plants like Fagonia indica Burm.f. (family Zygophyllaceae), which have the capability to grow in extremely hot sand desert, have been rarely understood. The de novo genome sequence of F. indica using the Illumina high-throughput sequencing technology determined 128,379 bp long cp genome, encode 115 unique coding genes. The present study added the evidence of the loss of a copy of the IR in the cp genome of the taxa capable to grow in the hot sand desert. The maximum likelihood analysis revealed two distinct sub-clades i.e. Krameriaceae and Zygophyllaceae of the order Zygophyllales, nested within fabids.