Biology subjects

Hsieh, Y. E.

Publications and source records attributed to Hsieh, Y. E..

3 recordsLinked to original sources

bioRxiv2024

Salinity impacted microbial carbonate precipitation mechanisms of modern microbialites in peritidal zone

Microbialites, ancient records of microbial activity, serve as significant indicators of environmental change. This study examined microbialites from the peritidal zone of three tide pools at Fongchueisha, Hengchun, Taiwan, to investigate the impact of salinity on microbial community composition and carbonate precipitation mechanisms. Microbial samples were collected across varying salinity gradients over multiple timepoints and analyzed using next-generation sequencing of bacterial 16S and eukaryotic 18S rRNA genes. Our findings reveal that the microbial communities in higher salinity environments exhibited significant shifts, with increased relative abundance of ureolytic bacteria and ammonifying microorganisms, such as Myxococcota and Actinobacteriota. This suggests the presence of diverse microbial carbonate precipitation mechanisms beyond photosynthesis, including ureolysis and ammonification. Furthermore, our results show that changes in the composition of cyanobacteria and diatoms were influenced by salinity, with heterocystous cyanobacteria (e.g., Nostocales) dominating low-salinity environments, and non-heterocystous cyanobacteria (e.g., Synechococcales) prevailing in higher salinity environments. Functional predictions reveal that microbial communities in high-salinity environments were enriched in anaerobic metabolic pathways, including pyruvate fermentation and the urea cycle. These findings highlight the significant role of salinity in influencing microbial composition and metabolic pathways, shaping carbonate precipitation processes in microbialites. ImportanceThe study focuses on the impact of environmental salinity on microbial community composition and carbonate precipitation mechanisms within modern microbialites, based on an analysis of samples from three tide pools with different salinity levels collected at five time points throughout the year. Using next-generation sequencing of bacterial 16S and eukaryotic 18S rRNA genes, we identified key shifts in microbial communities along salinity gradients and explored diverse microbial processes involved in carbonate precipitation. This work enhances our understanding of microbial ecosystems within modern microbialites and their response to environmental changes. Additionally, our study provides insight into ancient biogeochemical processes, with implications for interpreting microbial metabolism in carbonate precipitation across different salinity regimes.

microbiology↗

bioRxiv2023

Successive responses of three coral holobiont components (coral hosts, symbiotic algae, and bacteria) to daily temperature fluctuations

Coral reef ecosystems support over a quarter of the worlds marine life and play important ecological and economic roles. However, the increasingly severe weather events associated with ocean warming and climate change are believed to be rapidly altering the functions of coral reefs and their ecosystems. Corals and their associated microbiota form a "holobiont," which includes symbiotic algae and other associated microbiota dominated by bacteria. These microbiota have a direct relationship with the health of the coral host. Their composition is influenced by various environmental factors, such as increasing sea water temperatures. Previous studies of the effects of temperature changes on coral physiology and associated bacterial communities have been conducted based on stable water temperatures set by mean temperatures, or by slowly increasing/decreasing temperatures. However, the daily temperature fluctuations that corals experience in nature are not stable. Rather, there may be significant differences of up to 6{degrees}C in a single day. The current understanding of the effects of large daily temperature fluctuations on coral and associated bacterial community dynamics is limited. Hence, in this study, we conducted a four-week tank experiment using different large daily temperature fluctuations accompanied by continuous warming conditions to investigate the effects on two common reef-building corals, Stylophora pistillata and Pocillopora acuta, in Taiwan. During the experiment, the activity of coral host catalase was measured, the photosynthetic ability of symbiotic algae was recorded, and the variation in bacterial communities was analyzed using the V6-V8 region of 16S rDNA. According to the results, different parts of the holobionts of different coral species exhibited varying response rates to the continuous warming conditions and diurnal temperature fluctuations. Additionally, it was found that diurnal temperature fluctuations may mitigate the heat stress on the host and reduce the changes in bacterial response to warming. Furthermore, the holobionts of different coral species may adopt different adaptation and survival strategies in response to diurnal temperature fluctuations and warming. Finally, based on the response of these two coral species under the conditions of diurnal temperature fluctuations and continuous warming, Acinetobacter and Rhodobacteraceae were identified as potential indicator coral-associated bacteria. This is the first study to investigate the tripartite dynamic response of coral, symbiotic algae and bacteria to daily temperature fluctuations.

microbiology↗

bioRxiv2023

Comparative analysis of metabolic models of microbial communities reconstructed from automated tools and consensus approaches

Genome-scale metabolic models (GEMs) of microbial communities offer valuable insights into the functional capabilities of their members and facilitate the exploration of microbial interactions. These models are generated using different automated reconstruction tools, each relying on different biochemical databases that may affect the conclusions drawn from the in silico analysis. One way to address this problem is to employ a consensus reconstruction method that combines the outcomes of different reconstruction tools. Here, we conducted a comparative analysis of community models reconstructed from three automated tools, i.e. CarveMe, gapseq, and KBase, alongside a consensus approach, utilizing data from two marine bacterial communities. Our analysis revealed that these reconstruction approaches, while based on the same genomes, resulted in GEMs with varying numbers of genes and reactions as well as metabolic functionalities, attributed to the different databases employed. Further, our results indicated that the set of exchanged metabolites was more influenced by the reconstruction approach rather than the specific bacterial community investigated. This observation suggests a potential bias in predicting metabolite interactions using community GEMs. We also showed that consensus models encompassed a larger number of reactions and metabolites while concurrently reducing the presence of dead-end metabolites. Therefore, the usage of consensus models allows making full and unbiased use from aggregating genes from the different reconstructions in assessing the functional potential of metabolic communities. ImportanceOur study contributes significantly to the field of microbial community modeling through a comprehensive comparison of genome-scale metabolic models (GEMs) generated via various automated tools, including: CarveMe, gapseq, KBase, and a consensus approach. We revealed substantial structural disparities in model outcomes, primarily attributed to variations in the employed databases. A key finding underscored the substantial impact of the reconstruction approach on the set of exchanged metabolites, emphasizing the necessity for enhanced data integration strategies. The consensus models emerge as a powerful solution, exhibiting improved functional capabilities by encompassing a greater number of reactions, metabolites, and genes. This not only offers a more comprehensive representation of metabolic networks within bacterial communities but also shows promise in reducing variability for more accurate predictions of exchange metabolites. Overall, our research provides a critical framework for refining microbial community simulations, impacting fields from ecology to synthetic biology.

systems biology↗