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- M. H. Medema (Netherlands)
Microbial Communities and Microbiomes 01
- M. H. Medema (Netherlands)
Abstract
Abstract Body
Plants, fungi and bacteria produce a wealth of specialized metabolites, which are of great importance from both ecological and clinical perspectives. Due to the accelerated accumulation of omics data, computational methods have become more and more important to identify these molecules and to assess their biological activities. Here, I will highlight recent work performed in my research group on developing and applying these approaches to discover these molecules and the genes and pathways encoding their production, as well as to study their roles in microbe-microbe and host-microbe interactions in human, plant and animal microbiomes.
Microbial Communities and Microbiomes 02
- P. Dorrestein (United States of America)
MICROBIAL COMMUNITY ANALYSIS OF HYDROGEN PRODUCER THERMOPHILIC ISOLATES FROM LOCAL HOT SPRINGS WITH NANOPORE SEQUENCING
- I. Akacin (Turkey)
Abstract
Background and Aims
Exploring hot spring thermophilic communities and their potential use through metagenomics is crucial as these habitats host a variety of beneficial microorganisms living under extreme conditions including high temperatures, lack of oxygen and limited nutrients. Thermophilic microorganisms are reported to be capable of converting various carbon sources into biofuels. The main purpose of this study was to investigate the microbial profiles and green hydrogen production capacity of the thermophilic isolates of local hot springs.
Methods
Isolates were collected from 5 different hot springs (Temperature:38.0-77.3°C and pH:6.42-7.88). A metagenomic analysis was performed with 16S rRNA amplification products using a MinION Sequencer from Oxford Nanopore Technologies. Prokaryotic microbial profiling was acquired following the sequencing of samples from upstream, midstream and downstream of the hot spring. Two different 16S rRNA primers (universal and targeted) were used to differentiate bacterial and archaeal presence in thermal waters.
Results
Newly designed targeted primers demonstrated the presence of archaea and bacteria while universal primers only detected bacterial communities. A significant loss of microbial variety was observed as temperature decreased towards the edge of downstream hot spring. In contrast, the microbial-rich environment of upstream hot spring resulted in an increased hydrogen production of up to 90% conversion under anaerobic conditions maintained by 100% carbon monoxide gas at 60°C.
Conclusions
The outcomes of this study successfully demonstrated the adaptation of microorganisms to altered environmental conditions together with their biohydrogen production capacity.
GUT MICROBIOME OF AN ENDANGERED FISH: TOR PUTITORA (HAM.) AND ITS IMPLICATIONS ON HOST HEALTH
- R. K. Negi (India)
Abstract
Background and Aims
The gastrointestinal tract of vertebrates harbours pathogenic bacteria in addition to symbiotic bacteria. These symbiotic bacteria suppress the growth of opportunistic pathogens by competing for nutrients available in the host and by production of various antimicrobial peptides. Alteration to the normal gut microflora leads to diseased condition. Tor putitora is a large freshwater fish of the Indian subcontinent and is commonly found in the foothills of Himalaya with decent-sized populations in the Gobindsagar reservoir of the Sutlej river, Himachal Pradesh, India. Commonly known as golden mahseer, this species was enlisted endangered in the International Union for Conservation of Nature and Natural Resources assessment year (2010). This necessitated the need for deciphering the microbial diversity associated with its gut and their functional aspects.
Methods
Shotgun metagenomics approach was employed to explore the composition and function of the microbial communities present in the gut of Tor putitora.
Results
The taxonomic diversity was mainly composed of Proteobacteria with predominance of genera Escherichia, Klebsiella and Aeromonas. The reconstruction of Aeromonas sp. and the genes for its secretion system also helped in enumeration of the intricate mechanisms of host-pathogen relationships.
Conclusions
In lines with the in-silico analysis for understanding the microbial diversity, the genes for virulence factors and antibiotic resistance were also found enriched in the community suggesting the potential role of commercial fish and seafood as reservoirs for multi-drug resistant bacteria.
SPECIES ABUNDANCE CORRELATIONS CAN DISTINGUISH SOME INTERACTION TYPES IN MICROBIAL NETWORKS
- S. Pinto (Netherlands)
Abstract
Background and Aims
Metagenomics-based studies on communities of microorganisms are mostly limited to only a few samples in time, presenting mere ‘snapshots’ of the microbial ecosystem. Inferring interspecific interactions from such cross-sectional data is a daunting task and likely prone to bias, as the ‘true’ networks governing microbiome dynamics are often unknown. Common methods to infer microbial interactions are based on co-occurrence measures, such as correlations between bacterial phylogenetic groups. We tested whether such methods are useful tools in inferring interaction networks.
Methods
For this purpose, we simulated bacterial communities by means of the generalized Lotka-Volterra model, with variation in model parameters representing variability among hosts.
Results
Our results show that correlations can be indicative for presence of bacterial interactions, but only when measurement noise is low relative to the variation in interaction strengths between hosts. Indication of interaction was affected by type of interaction network, process noise and sampling under non-equilibrium conditions. Correlation sign mostly coincided with the strongest pairwise interaction. However, we found that competitive interactions can sometimes result in positive as well as negative correlations.
Conclusions
To summarize, correlations can distinguish some microbial interaction types, but careful interpretation and validation is required when inferring networks from cross-sectional abundance data.