Ammonium-Enhanced Arsenic Mobilization from Aquifer Sediments.

Ammonium-related pathways are important for groundwater arsenic (As) enrichment, especially via microbial Fe(III) reduction coupled with anaerobic ammonium oxidation; however, the key pathways (and microorganisms) underpinning ammonium-induced Fe(III) reduction and their contributions to As mobilization in groundwater are still unknown. To address this gap, aquifer sediments hosting high As groundwater from the western Hetao Basin were incubated with 15N-labeled ammonium and external organic carbon sources (including glucose, lactate, and lactate/acetate). Decreases in ammonium concentrations were positively correlated with increases in the total produced Fe(II) (Fe(II)tot) and released As. The molar ratios of Fe(II)tot to oxidized ammonium ranged from 3.1 to 3.7 for all incubations, and the δ15N values of N2 from the headspace increased in 15N-labeled ammonium-treated series, suggesting N2 as the key end product of ammonium oxidation. The addition of ammonium increased the As release by 16.1% to 49.6%, which was more pronounced when copresented with organic electron donors. Genome-resolved metagenomic analyses (326 good-quality MAGs) suggested that ammonium-induced Fe(III) reduction in this system required syntrophic metabolic interactions between bacterial Fe(III) reduction and archaeal ammonium oxidation. The current results highlight the significance of syntrophic ammonium-stimulated Fe(III) reduction in driving As mobilization, which is underestimated in high As groundwater.

Recovery of 1887 metagenome-assembled genomes from the South China Sea.

The South China Sea (SCS) is a marginal sea characterized by strong land-sea biogeochemical interactions. SCS has a distinctive landscape with a multitude of seamounts in its basin. Seamounts create "seamount effects" that influence the diversity and distribution of planktonic microorganisms in the surrounding oligotrophic waters. Although the vertical distribution and community structure of marine microorganisms have been explored in certain regions of the global ocean, there is a lack of comprehensive microbial genomic surveys for uncultured microorganisms in SCS, particularly in the seamount regions. Here, we employed a metagenomic approach to study the uncultured microbial communities sampled from the Xianbei seamount region to the North Coast waters of SCS. A total of 1887 non-redundant prokaryotic metagenome-assembled genomes (MAGs) were reconstructed, of which, 153 MAGs were classified as high-quality MAGs based on the MIMAG standards. The community structure and genomic information provided by this dataset could be used to analyze microbial distribution and metabolism in the SCS.

Depth-dependent microbial metagenomes sampled in the northeastern Indian Ocean.

The northeastern Indian Ocean exhibits distinct hydrographic characteristics influenced by various local and remote forces. Variations in these driving factors may alter the physiochemical properties of seawater, such as dissolved oxygen levels, and affect the diversity and function of microbial communities. How the microbial communities change across water depths spanning a dissolved oxygen gradient has not been well understood. Here we employed both 16S rDNA amplicon and metagenomic sequencing approaches to study the microbial communities collected from different water depths along the E87 transect in the northeastern Indian Ocean. Samples were collected from the surface, Deep Chlorophyll Maximum (DCM), Oxygen Minimum Zone (OMZ), and bathypelagic layers. Proteobacteria were prevalent throughout the water columns, while Thermoproteota were found to be abundant in the aphotic layers. A total of 675 non-redundant metagenome-assembled genomes (MAGs) were constructed, spanning 21 bacterial and 5 archaeal phyla. The community structure and genomic information provided by this dataset offer valuable resources for the analysis of microbial biogeography and metabolism in the northeastern Indian Ocean.

Identifying local associations in biological time series: algorithms, statistical significance, and applications.

Local associations refer to spatial-temporal correlations that emerge from the biological realm, such as time-dependent gene co-expression or seasonal interactions between microbes. One can reveal the intricate dynamics and inherent interactions of biological systems by examining the biological time series data for these associations. To accomplish this goal, local similarity analysis algorithms and statistical methods that facilitate the local alignment of time series and assess the significance of the resulting alignments have been developed. Although these algorithms were initially devised for gene expression analysis from microarrays, they have been adapted and accelerated for multi-omics next generation sequencing datasets, achieving high scientific impact. In this review, we present an overview of the historical developments and recent advances for local similarity analysis algorithms, their statistical properties, and real applications in analyzing biological time series data. The benchmark data and analysis scripts used in this review are freely available at http://github.com/labxscut/lsareview.

Virus impacted community adaptation in oligotrophic groundwater environment revealed by Hi-C coupled metagenomic and viromic study.

Viruses play a crucial role in microbial mortality, diversity and biogeochemical cycles. Groundwater is the largest global freshwater and one of the most oligotrophic aquatic systems on Earth, but how microbial and viral communities are shaped in this special habitat is largely unexplored. In this study, we collected groundwater samples from 23 to 60 m aquifers at Yinchuan Plain, China. In total, 1920 non-reductant viral contigs were retrieved from metagenomes and viromes constructed by Illumina and Nanopore hybrid sequencing. Only 3% of them could be clustered with known viruses, most of which were Caudoviricetes. Coupling 1.2 Tb Hi-C sequencing with CRISPR matching and homology search, we connected 469 viruses with their hosts while some viral clusters presented a broad-host-range trait. Meanwhile, a large proportion of biosynthesis related auxiliary metabolism genes were identified. Those characteristics might benefit viruses for a better survival in this special oligotrophic environment. Additionally, the groundwater virome showed genomic features distinct from those of the open ocean and wastewater treatment facilities in GC distribution and unannotated gene compositions. This paper expands the current knowledge of the global viromic records and serves as a foundation for a more thorough understanding of viruses in groundwater.

Complete Genome Sequence of Stutzerimonas stutzeri Strain SOCE 002, a Marine Bacterium Isolated from the Surface Seawater of Dapeng Bay.

We report the complete genome sequence of Stutzerimonas stutzeri strain SOCE 002, obtained from Illumina and Oxford Nanopore sequencing. The genome is 4.68 Mb long, with a GC content of 63.5%, and contains 4,334 protein-coding genes, 60 tRNAs, and 12 rRNAs. We expect that this complete genome sequence will provide a reference for both genomic and metabolic analyses of S. stutzeri.

Diversity and Distribution of Harmful Algal Bloom Species from Seamount to Coastal Waters in the South China Sea.

Mount Xianbei is one of the largest shallow seamounts located in the middle of the South China Sea (SCS), which might play a role in shaping the biodiversity of surrounding continental coastal waters, particularly the diversity of phytoplankton species causing frequent harmful algal blooms (HABs) in northern SCS. However, the diversity, composition, and distribution of phytoplankton species in the seamount regions of Xianbei remain largely unexplored. In this study, samples around and outside the seamount regions were collected during a late summer cruise of 2021 to test whether seamounts play a role in HAB species propagation. In total, we identified 19 HAB species across all samples using the ASV-based DNA metabarcoding approach, 6 of which had not been reported previously in the SCS, suggesting a diverse HAB species in the SCS. Specifically, 16 HAB species were found in the seamount region of Xianbei, and 5 of them were also found in the coastal waters, indicating a close connection between seamount and coastal waters. This study was the first attempt to explore HAB species' spatial diversity and vertical distribution in the seamount region of Xianbei at single-nucleotide resolution, which provides a novel explanation for the coastal HAB occurrence in the northern SCS. IMPORTANCE There are a number of seamounts under the water of the South China Sea (SCS). The seamounts might play a role in shaping the biodiversity of surrounding continental coastal waters. However, there is no direct evidence revealing the relationship of the biodiversity of phytoplankton between seamounts and coastal waters in the SCS, especially those species having the potential to form harmful algal blooms (HABs). Some HAB species might proliferate in certain geographic locations, while others may be broadly distributed across oceanic provinces. In this study, we provided a detailed analysis of phytoplankton composition and molecular detection of HAB species from seamount to coastal waters in the SCS, which suggested a strong interaction in the HAB species between the two areas. This finding provides new insights into the diversity and distribution of HABs in seamounts and their role in shaping the composition and the occurrence of HABs in coastal water.

Complete Genome Sequence of a Cognatishimia activa Strain Assembled from the Phycosphere of the Marine Diatom Skeletonema tropicum.

Cognatishimia activa, previously known as Thalassobius activus, has been frequently isolated from marine environments. Here, we present the complete genome sequence of C. activa strain SOCE 004, assembled from the phycosphere of a long-term laboratory-maintained culture of the diatom Skeletonema tropicum. The complete genome is 3,211,994 bp long, with an average G+C content of 53.69%. The genome contains 3,195 genes, including 3,133 protein-coding genes, 50 tRNAs, and 3 copies each of 5S, 16S, and 23S rRNA genes.

Size-fractionated microbiome observed during an eight-month long sampling in Jiaozhou Bay and the Yellow Sea.

Jiaozhou Bay is a typical semi-enclosed bay with a temperate climate imposed by strong anthropogenic influence. To investigate microbial biodiversity and ecosystem services in this highly dynamic coastal environment, we conducted a monthly microbial survey spanning eight months at two stations in the bay and the open Yellow Sea starting in April 2015. This report provides a comprehensive inventory of amplicon sequences and environmental microbial genomes from this survey. In total, 2,543 amplicon sequence variants were obtained with monthly relative abundance profiles in three size fractions (>2.7 µm, 2.7-0.7 µm, and 0.7-0.22 µm). Shotgun metagenomes yielded 915 high-quality metagenome-assembled genomes with ≥50% completeness and ≤5% contamination. These environmental genomes comprise 27 bacterial and 5 archaeal phyla. We expect this comprehensive dataset will facilitate a better understanding of coastal microbial ecology.

Effects of Temperature on Transparent Exopolymer Particle Production and Organic Carbon Allocation of Four Marine Phytoplankton Species.

Transparent exopolymer particles (TEP) are sticky polymeric substances that are commonly found in the periphery of microbial cells or colonies. They can naturally flocculate smaller suspended particles into larger aggregates and thus play a crucial role in the biological pump and the global carbon cycle. Phytoplankton are the major contributors to marine TEP production, whereas the way TEP production interacts with abiotic factors at the species level is generally unknown but critical for estimating carbon fluxes. In this study, the effects of temperature on TEP production and carbon allocation were studied in two representative diatom species (Nitzschia closterium and Chaetoceros affinis) and two model dinoflagellate species (Prorocentrum micans and Scrippisella trichoidea). The results showed that temperature had a significant impact on TEP production in all species. First, increased temperature promoted the TEP production of all four species. Second, elevated temperature affected the carbon pool allocation, with enhanced dissolved organic carbon (DOC) exudation in the form of TEP in all species. The TEP-C/DOC percentages of N. closterium and P. micans were 93.42 ± 5.88% and 82.03 ± 21.36% at the highest temperature (24 °C), respectively, which was approximately two to five times higher than those percentages at 16 °C. In contrast, TEP's contribution to the POC pool is lower than that to the DOC pool, ranging from 6.74 ± 0.79% to 28.31 ± 1.79% for all species. Moreover, phytoplankton TEP production may be related to cellular size and physiology. The TEP content produced by the smallest N. closterium (218.96 ± 15.04 fg Xeq./µm3) was ~5 times higher compared to P. micans, S. trichoidea, or C. affinis. In conclusion, TEP production is temperature sensitive and species specific, which should be taken into consideration the regarding TEP-mediated oceanic carbon cycle, particularly in the context of global warming.

Phage-bacterial contig association prediction with a convolutional neural network.

MOTIVATION: Phage-host associations play important roles in microbial communities. But in natural communities, as opposed to culture-based lab studies where phages are discovered and characterized metagenomically, their hosts are generally not known. Several programs have been developed for predicting which phage infects which host based on various sequence similarity measures or machine learning approaches. These are often based on whole viral and host genomes, but in metagenomics-based studies, we rarely have whole genomes but rather must rely on contigs that are sometimes as short as hundreds of bp long. Therefore, we need programs that predict hosts of phage contigs on the basis of these short contigs. Although most existing programs can be applied to metagenomic datasets for these predictions, their accuracies are generally low. Here, we develop ContigNet, a convolutional neural network-based model capable of predicting phage-host matches based on relatively short contigs, and compare it to previously published VirHostMatcher (VHM) and WIsH. RESULTS: On the validation set, ContigNet achieves 72-85% area under the receiver operating characteristic curve (AUROC) scores, compared to the maximum of 68% by VHM or WIsH for contigs of lengths between 200 bps to 50 kbps. We also apply the model to the Metagenomic Gut Virus (MGV) catalogue, a dataset containing a wide range of draft genomes from metagenomic samples and achieve 60-70% AUROC scores compared to that of VHM and WIsH of 52%. Surprisingly, ContigNet can also be used to predict plasmid-host contig associations with high accuracy, indicating a similar genetic exchange between mobile genetic elements and their hosts. AVAILABILITY AND IMPLEMENTATION: The source code of ContigNet and related datasets can be downloaded from https://github.com/tianqitang1/ContigNet.

Genomic and transcriptomic insights into the habitat adaptation of the diazotrophic paddy-field cyanobacterium Nostoc sphaeroides.

Nitrogen-fixing cyanobacteria are common in paddy fields, one of the most productive wetland ecosystems. Here, we present the complete genome of Nostoc sphaeroides, a paddy-field diazotroph used for food and medicine for more than 1700 years and deciphered the transcriptional regulation during the developmental transition from hormogonia to vegetative filaments with heterocysts. The genome of N. sphaeroides consists of one circular chromosome (6.48 Mb), one of the largest ever reported megaplasmids (2.34 Mb), and seven plasmids. Multiple gene families involved in the adaption to high solar radiation and water fluctuation conditions were found expanded, while genes involved in anoxic adaptation and phosphonate utilization are located on the megaplasmid, suggesting its indispensable role in environmental adaptation. Distinct gene expression patterns were observed during the light-intensity-regulated transition from hormogonia to vegetative filaments, specifically, genes encoding proteins involved in photosynthetic light reaction, carbon fixation, nitrogen metabolism and heterocyst differentiation were significantly upregulated, whereas genes related to cell motility were down-regulated. Our results provide genomic and transcriptomic insights into the adaptation of a filamentous nitrogen-fixing cyanobacterium to the highly dynamic paddy-field habitat, suggesting N. sphaeroides as an excellent system to understand the transition from aquatic to terrestrial habitats and to support sustainable rice production.

Estimating maximal microbial growth rates from cultures, metagenomes, and single cells via codon usage patterns.

Maximal growth rate is a basic parameter of microbial lifestyle that varies over several orders of magnitude, with doubling times ranging from a matter of minutes to multiple days. Growth rates are typically measured using laboratory culture experiments. Yet, we lack sufficient understanding of the physiology of most microbes to design appropriate culture conditions for them, severely limiting our ability to assess the global diversity of microbial growth rates. Genomic estimators of maximal growth rate provide a practical solution to survey the distribution of microbial growth potential, regardless of cultivation status. We developed an improved maximal growth rate estimator and predicted maximal growth rates from over 200,000 genomes, metagenome-assembled genomes, and single-cell amplified genomes to survey growth potential across the range of prokaryotic diversity; extensions allow estimates from 16S rRNA sequences alone as well as weighted community estimates from metagenomes. We compared the growth rates of cultivated and uncultivated organisms to illustrate how culture collections are strongly biased toward organisms capable of rapid growth. Finally, we found that organisms naturally group into two growth classes and observed a bias in growth predictions for extremely slow-growing organisms. These observations ultimately led us to suggest evolutionary definitions of oligotrophy and copiotrophy based on the selective regime an organism occupies. We found that these growth classes are associated with distinct selective regimes and genomic functional potentials.

Benchmarking microbial growth rate predictions from metagenomes.

Growth rates are central to understanding microbial interactions and community dynamics. Metagenomic growth estimators have been developed, specifically codon usage bias (CUB) for maximum growth rates and "peak-to-trough ratio" (PTR) for in situ rates. Both were originally tested with pure cultures, but natural populations are more heterogeneous, especially in individual cell histories pertinent to PTR. To test these methods, we compared predictors with observed growth rates of freshly collected marine prokaryotes in unamended seawater. We prefiltered and diluted samples to remove grazers and greatly reduce virus infection, so net growth approximated gross growth. We sampled over 44 h for abundances and metagenomes, generating 101 metagenome-assembled genomes (MAGs), including Actinobacteria, Verrucomicrobia, SAR406, MGII archaea, etc. We tracked each MAG population by cell-abundance-normalized read recruitment, finding growth rates of 0 to 5.99 per day, the first reported rates for several groups, and used these rates as benchmarks. PTR, calculated by three methods, rarely correlated to growth (r ~-0.26-0.08), except for rapidly growing γ-Proteobacteria (r ~0.63-0.92), while CUB correlated moderately well to observed maximum growth rates (r = 0.57). This suggests that current PTR approaches poorly predict actual growth of most marine bacterial populations, but maximum growth rates can be approximated from genomic characteristics.

Intensive land uses modify assembly process and potential metabolic function of edaphic bacterial communities in the Yellow River Delta, China.

Coastal reclamation is a global threat to natural ecosystems, disturbing biological community structure, diversity and ecological function through habitat conversion. We have limited insights into the changes brought about by coastal reclamation for different land-use types. We used the Yellow River Delta (YRD) as a model because it is a region with intensive land reclamation, and we investigated the structural and functional variations of bacterial communities and their relations to edaphic properties under different land-use types. Our results showed that the high soil organic carbon (SOC), nitrate concentrations and salinity were found in oil field, aquaculture pond and salt pan, respectively, and low values in natural wetland. Land use was found to have significant influence on bacterial community diversity. To investigate the phylogenetic conservation of specific traits, we analyzed the relationship between soil bacterial assembly processes and edaphic properties. Bacterial traits phylogenetically conserved, and differs in depth. Our findings suggest that SOC served as a deep trait due to it negative correlation with deeper branches of phylogenetic clustering, while nitrate functioned as a shallow trait due to its positive correlation with phylogenetic clustering at finer branches. Soil salinity acted as a complex trait effected on both finer and deeper branches. Further potential functional gene co-occurrence network analysis revealed that land reclamation induced shifts of metabolic function by altering the functional gene connectivity. We found that the photosynthesis pathway was enriched in hub modules related to oil field (OF), while methane metabolism was enriched in hub modules linked to sea cucumber pond (CP1). In addition, two-component systems (TCS) were enriched with nitrate, ammonia, SOC and salinity-related modules. Therefore, our study highlights the importance of integrating multi-function and multi-process identification and prediction of coastal diverse reclamation impacts on coastal ecosystems.

The power of cooperation: Experimental and computational approaches in the functional characterization of bacterial sRNAs.

Trans-acting small regulatory RNAs (sRNAs) are key players in the regulation of gene expression in bacteria. There are hundreds of different sRNAs in a typical bacterium, which in contrast to eukaryotic microRNAs are more heterogeneous in length, sequence composition, and secondary structure. The vast majority of sRNAs function post-transcriptionally by binding to other RNAs (mRNAs, sRNAs) through rather short regions of imperfect sequence complementarity. Besides, every single sRNA may interact with dozens of different target RNAs and impact gene expression either negatively or positively. These facts contributed to the view that the entirety of the regulatory targets of a given sRNA, its targetome, is challenging to identify. However, recent developments show that a more comprehensive sRNAs targetome can be achieved through the combination of experimental and computational approaches. Here, we give a short introduction into these methods followed by a description of two sRNAs, RyhB, and RsaA, to illustrate the particular strengths and weaknesses of these approaches in more details. RyhB is an sRNA involved in iron homeostasis in Enterobacteriaceae, while RsaA is a modulator of virulence in Staphylococcus aureus. Using such a combined strategy, a better appreciation of the sRNA-dependent regulatory networks is now attainable.

Insight into the genome and brackish water adaptation strategies of toxic and bloom-forming Baltic Sea Dolichospermum sp. UHCC 0315.

The Baltic Sea is a shallow basin of brackish water in which the spatial salinity gradient is one of the most important factors contributing to species distribution. The Baltic Sea is infamous for its annual cyanobacterial blooms comprised of Nodularia spumigena, Aphanizomenon spp., and Dolichospermum spp. that cause harm, especially for recreational users. To broaden our knowledge of the cyanobacterial adaptation strategies for brackish water environments, we sequenced the entire genome of Dolichospermum sp. UHCC 0315, a species occurring not only in freshwater environments but also in brackish water. Comparative genomics analyses revealed a close association with Dolichospermum sp. UHCC 0090 isolated from a lake in Finland. The genome closure of Dolichospermum sp. UHCC 0315 unraveled a mixture of two subtypes in the original culture, and subtypes exhibited distinct buoyancy phenotypes. Salinity less than 3 g L-1 NaCl enabled proper growth of Dolichospermum sp. UHCC 0315, whereas growth was arrested at moderate salinity (6 g L-1 NaCl). The concentrations of toxins, microcystins, increased at moderate salinity, whereas RNA sequencing data implied that Dolichospermum remodeled its primary metabolism in unfavorable high salinity. Based on our results, the predicted salinity decrease in the Baltic Sea may favor toxic blooms of Dolichospermum spp.