A culture-independent approach, supervised machine learning, and the characterization of the microbial community composition of coastal areas across the Bay of Bengal and the Arabian Sea

BACKGROUND

Coastal areas are subject to various anthropogenic and natural influences. In this study, we investigated and compared the characteristics of two coastal regions, Andhra Pradesh (AP) and Goa (GA), focusing on pollution, anthropogenic activities, and recreational impacts. We explored three main factors influencing the differences between these coastlines: The Bay of Bengal's shallower depth and lower salinity; upwelling phenomena due to the thermocline in the Arabian Sea; and high tides that can cause strong currents that transport pollutants and debris.

RESULTS

The microbial diversity in GA was significantly higher than that in AP, which might be attributed to differences in temperature, soil type, and vegetation cover. 16S rRNA amplicon sequencing and bioinformatics analysis indicated the presence of diverse microbial phyla, including candidate phyla radiation (CPR). Statistical analysis, random forest regression, and supervised machine learning models classification confirm the diversity of the microbiome accurately. Furthermore, we have identified 450 cultures of heterotrophic, biotechnologically important bacteria. Some strains were identified as novel taxa based on 16S rRNA gene sequencing, showing promising potential for further study.

CONCLUSION

Thus, our study provides valuable insights into the microbial diversity and pollution levels of coastal areas in AP and GA. These findings contribute to a better understanding of the impact of anthropogenic activities and climate variations on biology of coastal ecosystems and biodiversity.

Common scab disease-induced changes in geocaulosphere microbiome assemblages and functional processes in landrace potato (Solanum tuberosum var. Rongpuria) of Assam, India

Common scab (CS) caused by pathogenic Streptomyces spp. plays a decisive role in the qualitative and quantitative production of potatoes worldwide. Although the CS pathogen is present in Assam's soil, disease signs and symptoms are less obvious in the landrace Rongpuria potatoes that indicate an interesting interaction between the plant and the geocaulosphere microbial population. Toward this, a comparative metagenomics study was performed to elucidate the geocaulosphere microbiome assemblages and functions of low CS-severe (LSG) and moderately severe (MSG) potato plants. Alpha diversity indices showed that CS occurrence modulated microbiome composition and decreased overall microbial abundances. Functional analysis involving cluster of orthologous groups (COG) too confirmed reduced microbial metabolism under disease incidence. The top-three most dominant genera were Pseudomonas (relative abundance: 2.79% in LSG; 12.31% in MSG), Streptomyces (2.55% in LSG; 5.28% in MSG), and Pantoea (2.30% in LSG; 3.51% in MSG). As shown by the high Pielou's J evenness index, the potato geocaulosphere core microbiome was adaptive and resilient to CS infection. The plant growth-promoting traits and potential antagonistic activity of major taxa (Pseudomonads, non-pathogenic Streptomyces spp., and others) against the CS pathogen, i.e., Streptomyces scabiei, point toward selective microbial recruitment and colonization strategy by the plants to its own advantage. KEGG Orthology analysis showed that the CS infection resulted in high abundances of ATP-binding cassette transporters and a two-component system, ubiquitous to the transportation and regulation of metabolites. As compared to the LSG metagenome, the MSG counterpart had a higher representation of important PGPTs related to 1-aminocyclopropane-1-carboxylate deaminase, IAA production, betaine utilization, and siderophore production.