Linking plant functional genes to rhizosphere microbes: a review.

The importance of rhizomicrobiome in plant development, nutrition acquisition and stress tolerance is unquestionable. Relevant plant genes corresponding to the above functions also regulate rhizomicrobiome construction. Deciphering the molecular regulatory network of plant-microbe interactions could substantially contribute to improving crop yield and quality. Here, the plant gene-related nutrient uptake, biotic and abiotic stress resistance, which may influence the composition and function of microbial communities, are discussed in this review. In turn, the influence of microbes on the expression of functional plant genes, and thereby plant growth and immunity, is also reviewed. Moreover, we have specifically paid attention to techniques and methods used to link plant functional genes and rhizomicrobiome. Finally, we propose to further explore the molecular mechanisms and signalling pathways of microbe-host gene interactions, which could potentially be used for managing plant health in agricultural systems.

Identifying and Understanding Microbial Methanogenesis in CO2 Storage.

Carbon capture and storage (CCS) is an important component in many national net-zero strategies. Ensuring that CO2 can be safely and economically stored in geological systems is critical. To date, CCS research has focused on the physiochemical behavior of CO2, yet there has been little consideration of the subsurface microbial impact on CO2 storage. However, recent discoveries have shown that microbial processes (e.g., methanogenesis) can be significant. Importantly, methanogenesis may modify the fluid composition and the fluid dynamics within the storage reservoir. Such changes may subsequently reduce the volume of CO2 that can be stored and change the mobility and future trapping systematics of the evolved supercritical fluid. Here, we review the current knowledge of how microbial methanogenesis could impact CO2 storage, including the potential scale of methanogenesis and the range of geologic settings under which this process operates. We find that methanogenesis is possible in all storage target types; however, the kinetics and energetics of methanogenesis will likely be limited by H2 generation. We expect that the bioavailability of H2 (and thus potential of microbial methanogenesis) will be greatest in depleted hydrocarbon fields and least within saline aquifers. We propose that additional integrated monitoring requirements are needed for CO2 storage to trace any biogeochemical processes including baseline, temporal, and spatial studies. Finally, we suggest areas where further research should be targeted in order to fully understand microbial methanogenesis in CO2 storage sites and its potential impact.

Microbial sequencing methods for monitoring of anaerobic treatment of antibiotics to optimize performance and prevent system failure.

As a result of developments in molecular technologies and the use of sequencing technologies, the analyses of the anaerobic microbial community in biological treatment process has become increasingly prevalent. This review examines the ways in which microbial sequencing methods can be applied to achieve an extensive understanding of the phylogenetic and functional characteristics of microbial assemblages in anaerobic reactor if the substrate is contaminated by antibiotics which is one of the most important toxic compounds. It will discuss some of the advantages and disadvantages associated with microbial sequencing techniques that are more commonly employed and will assess how a combination of the existing methods may be applied to develop a more comprehensive understanding of microbial communities and improve the validity and depth of the results for the enhancement of the stability of anaerobic reactors.

Artificial Intelligence in microbiomes analysis: A review of applications in dermatology.

Microorganisms are closely related to skin diseases, and microbiological imbalances or invasions of exogenous pathogens can be a source of various skin diseases. The development and prognosis of such skin diseases are also closely related to the type and composition ratio of microorganisms present. Therefore, through detection of the characteristics and changes in microorganisms, the possibility for diagnosis and prediction of skin diseases can be markedly improved. The abundance of microorganisms and an understanding of the vast amount of biological information associated with these microorganisms has been a formidable task. However, with advances in large-scale sequencing, artificial intelligence (AI)-related machine learning can serve as a means to analyze large-scales of data related to microorganisms along with determinations regarding the type and status of diseases. In this review, we describe some uses of this exciting, new emerging field. In specific, we described the recognition of fungi with convolutional neural networks (CNN), the combined application of microbial genome sequencing and machine learning and applications of AI in the diagnosis of skin diseases as related to the gut-skin axis.

Targeted rRNA depletion enables efficient mRNA sequencing in diverse bacterial species and complex co-cultures.

IMPORTANCE: Microbes present one of the most diverse sources of biochemistry in nature, and mRNA sequencing provides a comprehensive view of this biological activity by quantitatively measuring microbial transcriptomes. However, efficient mRNA capture for sequencing presents significant challenges in prokaryotes as mRNAs are not poly-adenylated and typically make up less than 5% of total RNA compared with rRNAs that exceed 80%. Recently developed methods for sequencing bacterial mRNA typically rely on depleting rRNA by tiling large probe sets against rRNAs; however, such approaches are expensive, time-consuming, and challenging to scale to varied bacterial species and complex microbial communities. Therefore, we developed EMBR-seq+, a method that requires fewer than 10 short oligonucleotides per rRNA to achieve up to 99% rRNA depletion in diverse bacterial species. Finally, EMBR-seq+ resulted in a deeper view of the transcriptome, enabling systematic quantification of how microbial interactions result in altering the transcriptional state of bacteria within co-cultures.

Entirely Off-Grid and Solar-Powered DNA Sequencing of Microbial Communities during an Ice Cap Traverse Expedition.

Microbial communities in remote locations remain under-studied. This is particularly true on glaciers and icecaps, which cover approximately 11% of the Earth's surface. The principal reason for this is the inaccessibility of most of these areas due to their extreme isolation and challenging environmental conditions. While remote research stations have significantly lowered the barrier to studying the microbial communities on icecaps, their use has led to a bias for data collection in the near vicinity of these institutions. Here, miniaturisation of a DNA sequencing lab suitable for off-grid metagenomic studies is demonstrated. Using human power alone, this lab was transported across Europe's largest ice cap (Vatnajökull, Iceland) by ski and sledge. After 11 days of unsupported polar-style travel, a metagenomic study of a geothermal hot spring gorge was conducted on the remote northern edge of the ice cap. This tent-based metagenomic study resulted in over 24 h of Nanopore sequencing, powered by solar power alone. This study demonstrates the ability to conduct DNA sequencing in remote locations, far from civilised resources (mechanised transport, external power supply, internet connection, etc.), whilst greatly reducing the time from sample collection to data acquisition.