Microbial anaerobic metabolism is a key driver of biogeochemical cycles, influencing ecosystem function and health of both natural and engineered environments. However, the temporal dynamics of the intricate interactions between microorganisms and the organic metabolites are still poorly understood. Leveraging metagenomic and metabolomic approaches, we unveiled the principles governing microbial metabolism during a 96-day anaerobic bioreactor experiment. 

Unveiling the deterministic dynamics of microbial meta-metabolism: a multi-omics investigation of anaerobic biodegradation

Microbial communities are shaped by the complex interactions among organisms and the environment. Genome-scale metabolic models (GEMs) can provide deeper insights into the complexity and ecological properties of various microbial communities, revealing their intricate interactions. Many researchers have modified GEMs for the microbial communities based on specific needs. Thus, GEMs need to be comprehensively summarized to better understand the trends in their development. In this review, we summarized the key developments in deciphering and designing microbial communities using different GEMs. A timeline of selected highlights in GEMs indicated that this area is evolving from the single-strain level to the microbial community level. Then, we outlined a framework for constructing GEMs of microbial communities. We also summarized the models and resources of static and dynamic community-level GEMs. We focused on the role of external environmental and intracellular resources in shaping the assembly of microbial communities. Finally, we discussed the key challenges and future directions of GEMs, focusing on the integration of GEMs with quorum sensing mechanisms, microbial ecology interactions, machine learning algorithms, and automatic modeling, all of which contribute to consortia-based applications in different fields. 

Deciphering and designing microbial communities by genome-scale metabolic modelling

Water contamination with heavy metals seriously affects water and sediment quality and may affect the aquatic biota. This study assessed the impact of heavy metals on the morphological characteristics of aquatic microorganisms in potentially contaminated water. Different physicochemical parameters and heavy metals contents were analyzed for toxicological assessment along with microbial diversity in the rivers Swat and Kabul. The pH of River Swat water was neutral to slightly alkaline, while River Kabul was neutral to slightly acidic. The results showed substantial variations in heavy metal concentration across different sampling points. In both River Swat and River Kabul water samples, Cu and Zn concentrations were below the permissible limits for surface and drinking water qualities while the rest of the heavy metals exceeded the permissible limit with Cd being the most abundant heavy metal. Similarly, in sediment samples all the heavy metals were below the permissible limits except for Cd that exceeded the Environment Canada (EC) limits in River Swat and EC and NOVA limits in River Kabul. The rest of the heavy metals concentrations were within the permissible limits, with few exceptions. The results showed that in River Swat, most of the contamination was of geogenic origin, while the main source of contamination in River Kabul was anthropogenic. Results of microbial analysis showed that River Swat has more diversity than River Kabul, which may be due to the low contamination profile of River Swat. It was further observed that high heavy metal concentrations negatively impact the morphological characteristics of microorganisms. The heavy metals concentration and microbial diversity were closely related to each other.

Heavy Metals and Microbial Diversity: A Comparative Analysis of Rivers Swat and Kabul

Maize is one of the major crops cultivated in northern Shandong Province and contributes significantly to China's maize production, and nitrogen (N) application to the soil can have a marked impact on maize yield and soil microbial productivity. The current environmental challenge, which needs urgently to be addressed, is to effectively utilize fertilizer nitrogen to improve crop production without causing environmental stress in sustainable agroecosystems. Soil fungi can improve plant health and crop performance through improved nutrient uptake and reducing plant stress levels. How soil N influences fungal diversity and maize yield at spatial patterns remains unclear. In this study, the influences of different soil N treatments on maize yields and fungal diversity were investigated in maize fields at five N rates (from 0 to 120 kg ha−1). High-throughput sequencing of the internal transcribed spacer (ITS) region revealed that α- and β-diversities of fungi significantly increased at 80 kg N ha−1 (N80) but decreased significantly in the control (N0) and other N treatments. Variations in the NC model predicted strong fungal distribution patterns (R2 = 0.60) among all the treatments. The highest proportion of operational taxonomic units (OTUs) (68.99%) was observed at N80. The study also found that the complexity of the co-occurrence network significantly stabilized at N80, but a decrease in network complexity was observed at N120. The study showed that, relative to the control, the addition of N to the soil significantly increased the abundance of Ascomycota at the phylum level and Chaetomium, Fusarium, and Mortierella at the genus levels, with average abundances of 5.82%, 1.67%, and 19.58%, respectively. Functional ecology analysis indicated that soil N upregulated the composition of ecological fungal communities by stochastic processes. The composition of major fungal sub-communities was positively correlated with nitrogen/carbon cycling at N80. Moreover, results also indicated that the yields (3.14 t ha−1) and other agronomic effects at N80 were significantly higher than those in the other treatments. This study demonstrates that optimal nitrogen application achieves increases in both fungal diversity and yield, contributing to improved crop production and sustainability at spatial scales. 

Impact of nitrogen fertilizer application on soil fungal diversity and maize yield variation in Shandong Province, China

The intricate interplay between SMCs and agroecosystems has garnered substantial attention in recent decades due to its profound implications for agricultural productivity, ecosystem sustainability, and environmental health. Understanding the distribution of SMCs is complemented by investigations into their functional roles within agroecosystems. Soil microbes play pivotal roles in nutrient cycling, organic matter decomposition, disease suppression, and plant‒microbe interactions, profoundly influencing soil fertility, crop productivity, and ecosystem resilience. Elucidating the functional diversity and metabolic potential of SMCs is crucial for designing sustainable agricultural practices that harness the beneficial functions of soil microbes while minimizing detrimental impacts on ecosystem services. Various molecular techniques, such as next-generation sequencing and high-throughput sequencing, have facilitated the elucidation of microbial community structures and dynamics at different spatial scales. These efforts have revealed the influence of factors such as soil type, land management practices, climate, and land use change on microbial community composition and diversity. Advances in high-throughput methodological strategies have revolutionized our ability to characterize SMCs comprehensively and efficiently. These include amplicon sequencing, metagenomics, metatranscriptomics, and metaproteomics, which provide insights into microbial taxonomic composition, functional potential, gene expression, and protein profiles. The integration of multiomics approaches allows for a more holistic understanding of the complex interactions within SMCs and their responses to environmental perturbations. In conclusion, this review highlights the significant progress made in mapping, understanding the distribution, elucidating the functions, and employing high-throughput methodological strategies to study SMCs in agroecosystems. 

Mapping, Distribution, Function, and High-Throughput Methodological Strategies for Soil Microbial Communities in the Agroecosystem in the Last Decades

Spatial distribution patterns across multiple microbial taxonomic groups.

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Spatial distribution patterns across multiple microbial taxonomic groups.