Trimming and Validation of Illumina Short Reads Using Trimmomatic, Trinity Assembly, and Assessment of RNA-Seq Data

Phylogenomics and functional analysis of Glycerol-3-Phosphate Acyltransferase (GPAT) Genes: A critical role in lipid biosynthesis

The tung tree (Vernicia fordii Hemsl.), an economically important woody plant, is widely planted for the production of high-quality tung oil. Glycerol-3-phosphate acyltransferases (GPATs), the rate-limiting enzymes in triacylglycerol synthesis, play an important role in seed oil biosynthesis. In this study, we performed a genome-wide analysis of VfGPATs. A total of 9 VfGPATs were identified from the whole tung genome, and phylogenetic analysis divided the VfGPATs into three major clades: clade II (VfGPAT9), clade III (VfATS1) and clade IV (VfGPAT1 ~ 8). Subcellular localization analysis revealed that five VfGPATs (1, 5, 6, 8, and 9) are localized in the endoplasmic reticulum, and four VfGPATs (3-1, 3-2, 3-3, and ATS1) are localized in the chloroplast. Overexpression of VfGPATs in Arabidopsis thaliana revealed that the oil content in VfGPAT8- and VfGPAT9-transgenic plants were significantly increased by 26.60 and 55.94% compared to the wild-type. Transient expression of VfGPAT8 + VfFADX and VfGPAT9 + VfFADX could promote the synthesis of α-eleostearic acid and enhance the accumulation of lipid droplets in tobacco (Nicotiana benthamiana) leaves. We further tested the enzymatic activities of VfGPAT8 and VfGPAT9 with the yeast double mutant strain ZAFU1. The results showed that VfGPAT8 complemented the phosphatidate biosynthetic defect in the double mutant, while VfGPAT9 could not, suggesting that VfGPAT8 has a high acetyltransferase activity. However, altering serine (S) residue at position 113 of VfGPAT9 to threonine (T) could restore its enzymatic activity. This study provided important insights into the evolutionary history of VfGPATs and will promote the genetic improvement of tung trees and related species.

Biofilm marker discovery with cloud-based dockerized metagenomics analysis of microbial communities

In an environment, microbes often work in communities to achieve most of their essential functions, including the production of essential nutrients. Microbial biofilms are communities of microbes that attach to a nonliving or living surface by embedding themselves into a self-secreted matrix of extracellular polymeric substances. These communities work together to enhance their colonization of surfaces, produce essential nutrients, and achieve their essential functions for growth and survival. They often consist of diverse microbes including bacteria, viruses, and fungi. Biofilms play a critical role in influencing plant phenotypes and human microbial infections. Understanding how these biofilms impact plant health, human health, and the environment is important for analyzing genotype-phenotype-driven rule-of-life functions. Such fundamental knowledge can be used to precisely control the growth of biofilms on a given surface. Metagenomics is a powerful tool for analyzing biofilm genomes through function-based gene and protein sequence identification (functional metagenomics) and sequence-based function identification (sequence metagenomics). Metagenomic sequencing enables a comprehensive sampling of all genes in all organisms present within a biofilm sample. However, the complexity of biofilm metagenomic study warrants the increasing need to follow the Findability, Accessibility, Interoperability, and Reusable (FAIR) Guiding Principles for scientific data management. This will ensure that scientific findings can be more easily validated by the research community. This study proposes a dockerized, self-learning bioinformatics workflow to increase the community adoption of metagenomics toolkits in a metagenomics and meta-transcriptomics investigation. Our biofilm metagenomics workflow self-learning module includes integrated learning resources with an interactive dockerized workflow. This module will allow learners to analyze resources that are beneficial for aggregating knowledge about biofilm marker genes, proteins, and metabolic pathways as they define the composition of specific microbial communities. Cloud and dockerized technology can allow novice learners-even those with minimal knowledge in computer science-to use complicated bioinformatics tools. Our cloud-based, dockerized workflow splits biofilm microbiome metagenomics analyses into four easy-to-follow submodules. A variety of tools are built into each submodule. As students navigate these submodules, they learn about each tool used to accomplish the task. The downstream analysis is conducted using processed data obtained from online resources or raw data processed via Nextflow pipelines. This analysis takes place within Vertex AI's Jupyter notebook instance with R and Python kernels. Subsequently, results are stored and visualized in Google Cloud storage buckets, alleviating the computational burden on local resources. The result is a comprehensive tutorial that guides bioinformaticians of any skill level through the entire workflow. It enables them to comprehend and implement the necessary processes involved in this integrated workflow from start to finish. This manuscript describes the development of a resource module that is part of a learning platform named "NIGMS Sandbox for Cloud-based Learning" https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.

Hybrid constructed wetlands and filamentous fungi for treatment of mixed sewage and industrial effluents

Developing countries face multifaceted problems of water pollution and futile measures to combat water pollution. This study was conducted to explore the potential application of sustainable nature-based solutions, hybrid constructed wetlands, and the application of filamentous fungi to treat polluted river water that receives sewage and industrial wastewater. A pilot-scale hybrid constructed wetland design comprising two types of floating plants in distinct tanks along with a floating wetland and a free-water surface wetland connected in series was commissioned and tested. The system successfully removed organic pollution (BOD 94% and COD 90%), nutrients (NH4-N and NO3-N 67% and PO4-P 81%), and heavy metals (Cr 75%, Ni 56%, and Fe 79%) in 40 h and showed a high buffering capacity to cope with the varying pollutant loads. Metagenomics analysis of treated and untreated samples of river water revealed a diversified spatial bacterial community with ~ 25% sequences related to sulfur-metabolizing bacteria, genus Sulfuricurvum. The application of an immobilized strain of A. niger as a mycoremediation technique was also tested. It successfully removed pollutants in the combined sewage and industrial wastewater present in river water: COD (96%), TSS (97%), NH4-N (65%), NO3-N (67%), and PO4-P (78%). This study demonstrated that hybrid constructed wetlands and mycoremediation can be used as sustainable wastewater treatment options in the local context and also in developing countries where most of the conventional wastewater treatment plants do not operate.

Transcriptomics analyses reveal the key genes involved in stamen petaloid formation in Alcea rosea L

Alcea rosea L. is a traditional flower with a long cultivation history. It is extensively cultivated in China and is widely planted in green belt parks or used as cut flowers and potted ornamental because of its rich colors and flower shapes. Double-petal A. rosea flowers have a higher aesthetic value compared to single-petal flowers, a phenomenon determined by stamen petaloid. However, the underlying molecular mechanism of this phenomenon is still very unclear. In this study, an RNA-based comparative transcriptomic analysis was performed between the normal petal and stamen petaloid petal of A. rosea. A total of 3,212 differential expressed genes (DEGs), including 2,620 up-regulated DEGs and 592 down-regulated DEGs, were identified from 206,188 unigenes. Numerous DEGs associated with stamen petaloid were identified through GO and KEGG enrichment analysis. Notably, there were 63 DEGs involved in the plant hormone synthesis and signal transduction, including auxin, cytokinin, gibberellin, abscisic acid, ethylene, brassinosteroid, jasmonic acid, and salicylic acid signaling pathway and 56 key transcription factors (TFs), such as MADS-box, bHLH, GRAS, and HSF. The identification of these DEGs provides an important clue for studying the regulation pathway and mechanism of stamen petaloid formation in A. rosea and provides valuable information for molecular plant breeding.

Modifications of lipid pathways restrict SARS-CoV-2 propagation in human induced pluripotent stem cell-derived 3D airway organoids

BACKGROUND

Modifications of lipid metabolism were closely associated with the manifestations and prognosis of coronavirus disease of 2019 (COVID-19). Pre-existing metabolic conditions exacerbated the severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection while modulations of aberrant lipid metabolisms alleviated the manifestations. To elucidate the underlying mechanisms, an experimental platform that reproduces human respiratory physiology is required.

METHODS

Here we generated induced pluripotent stem cell-derived airway organoids (iPSC-AOs) that resemble the human native airway. Single-cell sequencing (ScRNAseq) and microscopic examination verified the cellular heterogeneity and microstructures of iPSC-AOs, respectively. We subjected iPSC-AOs to SARS-CoV-2 infection and investigated the treatment effect of lipid modifiers statin drugs on viral pathogenesis, gene expression, and the intracellular trafficking of the SARS-CoV-2 entry receptor angiotensin-converting enzyme-2 (ACE-2).

RESULTS

In SARS-CoV-2-infected iPSC-AOs, immunofluorescence staining detected the SARS-CoV-2 spike (S) and nucleocapsid (N) proteins and bioinformatics analysis further showed the aberrant enrichment of lipid-associated pathways. In addition, SARS-CoV-2 hijacked the host RNA replication machinery and generated the new isoforms of a high-density lipoprotein constituent apolipoprotein A1 (APOA1) and the virus-scavenging protein deleted in malignant brain tumors 1 (DMBT1). Manipulating lipid homeostasis using cholesterol-lowering drugs (e.g. Statins) relocated the viral entry receptor angiotensin-converting enzyme-2 (ACE-2) and decreased N protein expression, leading to the reduction of SARS-CoV-2 entry and replication. The same lipid modifications suppressed the entry of luciferase-expressing SARS-CoV-2 pseudoviruses containing the S proteins derived from different SARS-CoV-2 variants, i.e. wild-type, alpha, delta, and omicron.

CONCLUSIONS

Together, our data demonstrated that modifications of lipid pathways restrict SARS-CoV-2 propagation in the iPSC-AOs, which the inhibition is speculated through the translocation of ACE2 from the cell membrane to the cytosol. Considering the highly frequent mutation and generation of SARS-CoV-2 variants, targeting host metabolisms of cholesterol or other lipids may represent an alternative approach against SARS-CoV-2 infection.

Keystone taxa enhance the stability of soil bacterial communities and multifunctionality under steelworks disturbance

Continuous discharge of wastewater, emissions, and solid wastes from steelworks poses environmental risks to ecosystems. However, the role of keystone taxa in maintaining multifunctional stability during environmental disturbances remains poorly understood. To address this, we investigated the community diversity, assembly mechanisms, and soil multifunctionality of soils collected from within the steelworks (I), within 2.5 km radius from the steelworks (E), and from an undisturbed area (CK) in Jiangsu Province, China, via 16 S rRNA sequencing. Significant differences were found in the Chao1 and the richness indexes of the total taxa (p < 0.05), while the diversity of keystone taxa was not significant at each site (p > 0.05). The deterministic processes for total taxa were 42.9%, 61.9% and 47.7% in CK, E, and I, respectively. Steelworks stress increased the deterministicity of keystone taxa from 52.3% in CK to 61.9% in E and I soils. The average multifunctionality indices were 0.518, 0.506 and 0.513 for CK, E and I, respectively. Although the soil multifunctionality was positive correlated with α diversity of both the total and keystone taxa, the average degree of keystone taxa in functional network increased significantly (79.96 and 65.58, respectively), while the average degree of total taxa decreased (44.59 and 51.25, respectively) in the E and I. This suggests keystone taxa contribute to promoting the stability of ecosystems. With increasing disturbance, keystone taxa shift their function from basic metabolism (ribosome biogenesis) to detoxification (xenobiotics biodegradation, metabolism, and benzoate degradation). Here we show that keystone taxa are the most important factor in maintaining stable microbial communities and functions, providing new insights for mitigating pollution stress and soil health protection.

SETD2 mutations do not contribute to clonal fitness in response to chemotherapy in childhood B cell acute lymphoblastic leukemia

Mutations in genes encoding epigenetic regulators are commonly observed at relapse in B cell acute lymphoblastic leukemia (B-ALL). Loss-of-function mutations in SETD2, an H3K36 methyltransferase, have been observed in B-ALL and other cancers. Previous studies on mutated SETD2 in solid tumors and acute myelogenous leukemia support a role in promoting resistance to DNA damaging agents. We did not observe chemoresistance, an impaired DNA damage response, nor increased mutation frequency in response to thiopurines using CRISPR-mediated knockout in wild-type B-ALL cell lines. Likewise, restoration of SETD2 in cell lines with hemizygous mutations did not increase sensitivity. SETD2 mutations affected the chromatin landscape and transcriptional output that was unique to each cell line. Collectively our data does not support a role for SETD2 mutations in driving clonal evolution and relapse in B-ALL, which is consistent with the lack of enrichment of SETD2 mutations at relapse in most studies.

WASF3 overexpression affects the expression of circular RNA hsa-circ-0100153, which promotes breast cancer progression by sponging hsa-miR-31, hsa-miR-767-3p, and hsa-miR-935

Background

The WASF3 gene has been linked to promoting metastasis in breast cancer (BC) cells, and low expression reduces invasion potential. Circular RNAs (circRNAs) function as microRNA (miRNA) modulators and are involved in cancer progression, but the relationship between these factors remains unclear.

Methods

This study used bioinformatics methods and a computational approach to investigate the role of circRNAs and miRNAs in the context of WASF3 overexpression. Differentially expressed mRNAs, circRNAs, and miRNAs were identified using Gene Expression Omnibus (GEO) datasets. A competing endogenous RNA (ceRNA) network was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs. Functional and pathway enrichment analyses were predicted using a circRNA-miRNA-mRNA network.

Results

RNA expression patterns were significantly different between normal and tumor samples. A total of 190 circRNAs, 76 miRNAs, and 678 mRNAs were differentially expressed. The analysis of the circRNA-miRNA-mRNA regulatory network revealed interactions between hsa-circ-0100153, hsa-miR-31, hsa-miR-767-3p, and hsa-miR-935 with WASF3 in cancer. These interactions primarily function in DNA replication and the cell cycle.

Conclusions

This study reveals a mechanism by which WASF3 overexpression affects the expression of circRNAs hsa-circ-0100153, promoting BC progression by sponging hsa-miR-31/hsa-miR-767-3p /hsa-miR-935. This mechanism may increase the invasive potential of cancers, in addition to other reported molecular mechanisms involving the WASF3 gene.

Identification of the Light-Harvesting Chlorophyll a/b Binding Protein Gene Family in Peach (Prunus persica L.) and Their Expression under Drought Stress

In higher plants, light-harvesting chlorophyll a/b binding (Lhc) proteins play a vital role in photosynthetic processes and are widely involved in the regulation of plant growth, development, and response to abiotic stress. However, the Lhc gene family has not been well identified in peaches (Prunus persica L.). In this study, 19 PpLhc genes were identified in the peach genome database, which were unevenly distributed on all chromosomes. Phylogenetic analysis demonstrated that PpLhc proteins could be divided into three major subfamilies, each of whose members had different exon-intron structures but shared similar conserved motifs. A total of 17 different kinds of cis-regulatory elements were identified in the promoter regions of all PpLhc genes, which could be classified into three categories: plant growth and development, stress response, and phytohormone response. In addition, transcriptomic data analysis and RT-qPCR results revealed that the expression profiles of some PpLhc genes changed under drought treatment, suggesting the crucial roles of Lhc genes in the regulation of plant tolerance to drought stress. Taken together, these findings will provide valuable information for future functional studies of PpLhc genes, especially in response to drought stress.

Metagenomic evidence for antibiotics-driven co-evolution of microbial community, resistome and mobilome in hospital sewage

Overconsumption of antibiotics is an immediate cause for the emergence of antimicrobial resistance (AMR) and antibiotic resistant bacteria (ARB), though its environmental impact remains inadequately clarified. There is an urgent need to dissect the complex links underpinning the dynamic co-evolution of ARB and their resistome and mobilome in hospital sewage. Metagenomic and bioinformatic methods were employed to analyze the microbial community, resistome and mobilome in hospital sewage, in relation to data on clinical antibiotic use collected from a tertiary-care hospital. In this study, resistome (1,568 antibiotic resistance genes, ARGs, corresponding to 29 antibiotic types/subtypes) and mobilome (247 types of mobile genetic elements, MGEs) were identified. Networks connecting co-occurring ARGs with MGEs encompass 176 nodes and 578 edges, in which over 19 types of ARGs had significant correlations with MGEs. Prescribed dosage and time-dependent antibiotic consumption were associated with the abundance and distributions of ARGs, and conjugative transfer of ARGs via MGEs. Variation partitioning analyses show that effects of conjugative transfer were most likely the main contributors to transient propagation and persistence of AMR. We have presented the first evidence supporting idea that use of clinical antibiotics is a potent driving force for the development of co-evolving resistome and mobilome, which in turn supports the growth and evolution of ARB in hospital sewage. The use of clinical antibiotics calls for greater attention in antibiotic stewardship and management.

Discovering common pathogenic processes between COVID-19 and HFRS by integrating RNA-seq differential expression analysis with machine learning

Zoonotic virus spillover in human hosts including outbreaks of Hantavirus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) imposes a serious impact on the quality of life of patients. Recent studies provide a shred of evidence that patients with Hantavirus-caused hemorrhagic fever with renal syndrome (HFRS) are at risk of contracting SARS-CoV-2. Both RNA viruses shared a higher degree of clinical features similarity including dry cough, high fever, shortness of breath, and certain reported cases with multiple organ failure. However, there is currently no validated treatment option to tackle this global concern. This study is attributed to the identification of common genes and perturbed pathways by combining differential expression analysis with bioinformatics and machine learning approaches. Initially, the transcriptomic data of hantavirus-infected peripheral blood mononuclear cells (PBMCs) and SARS-CoV-2 infected PBMCs were analyzed through differential gene expression analysis for identification of common differentially expressed genes (DEGs). The functional annotation by enrichment analysis of common genes demonstrated immune and inflammatory response biological processes enriched by DEGs. The protein-protein interaction (PPI) network of DEGs was then constructed and six genes named RAD51, ALDH1A1, UBA52, CUL3, GADD45B, and CDKN1A were identified as the commonly dysregulated hub genes among HFRS and COVID-19. Later, the classification performance of these hub genes were evaluated using Random Forest (RF), Poisson Linear Discriminant Analysis (PLDA), Voom-based Nearest Shrunken Centroids (voomNSC), and Support Vector Machine (SVM) classifiers which demonstrated accuracy >70%, suggesting the biomarker potential of the hub genes. To our knowledge, this is the first study that unveiled biological processes and pathways commonly dysregulated in HFRS and COVID-19, which could be in the next future used for the design of personalized treatment to prevent the linked attacks of COVID-19 and HFRS.

The association of prokaryotic antiviral systems and symbiotic phage communities in drinking water microbiomes

Prokaryotic antiviral systems are important mediators for prokaryote-phage interactions, which have significant implications for the survival of prokaryotic community. However, the prokaryotic antiviral systems under environmental stress are poorly understood, limiting the understanding of microbial adaptability. Here, we systematically investigated the profile of the prokaryotic antiviral systems at the community level and prokaryote-phage interactions in the drinking water microbiome. Chlorine disinfectant was revealed as the main ecological driver for the difference in prokaryotic antiviral systems and prokaryote-phage interactions. Specifically, the prokaryotic antiviral systems in the microbiome exhibited a higher abundance, broader antiviral spectrum, and lower metabolic burden under disinfectant stress. Moreover, significant positive correlations were observed between phage lysogenicity and enrichment of antiviral systems (e.g., Type IIG and IV restriction-modification (RM) systems, and Type II CRISPR-Cas system) in the presence of disinfection, indicating these antiviral systems might be more compatible with lysogenic phages and prophages. Accordingly, there was a stronger prokaryote-phage symbiosis in disinfected microbiome, and the symbiotic phages carried more auxiliary metabolic genes (AMGs) related to prokaryotic adaptability as well as antiviral systems, which might further enhance prokaryote survival in drinking water distribution systems. Overall, this study demonstrates that the prokaryotic antiviral systems had a close association with their symbiotic phages, which provides novel insights into prokaryote-phage interactions and microbial environmental adaptation.

Exploring the mechanism of Self-Consistent balance between microbiota and high efficiency in wastewater treatment

Sewage treatment mediated by microbial organisms is a promising green trend. However, the complex balance between microbiota stability and highly efficient wastewater treatment requires investigation. This study successfully improved the effectiveness of sewage treatment by resetting the microbial community structure in the activated sludge. Truepera, Methylophaga, unclassified_Fodinicurvataceae, and unclassified_Actinomanarales were the dominant genera, while salinity and NH₃-N content were identified as the key environmental factors governing the microbial structure. By optimizing the microflora structure driven by environmental factors, the key minor genera were activated and coordinated with the aforementioned genera, thereby promoting wastewater treatment. Finally, the chemical oxygen demand, NH₃-N, and total phosphorus removal rates were improved to 86.8 ± 1.9%, 82.4 ± 4.1%, and 94.8 ± 3.8%, respectively. It provides a new insight to improve the wastewater treatment through setting microbiota by environmental factor driven.

An Environmental DNA Primer for Microbial and Restoration Ecology

Environmental DNA (eDNA) sequencing-DNA collected from the environment from living cells or shed DNA-was first developed for working with microbes and has greatly benefitted microbial ecologists for decades since. These tools have only become increasingly powerful with the advent of metabarcoding and metagenomics. Most new studies that examine diverse assemblages of bacteria, archaea, protists, fungi, and viruses lean heavily into eDNA using these newer technologies, as the necessary sequencing technology and bioinformatic tools have become increasingly affordable and user friendly. However, eDNA methods are rapidly evolving, and sometimes it can feel overwhelming to simply keep up with the basics. In this review, we provide a starting point for microbial ecologists who are new to DNA-based methods by detailing the eDNA methods that are most pertinent, including study design, sample collection and storage, selecting the right sequencing technology, lab protocols, equipment, and a few bioinformatic tools. Furthermore, we focus on how eDNA work can benefit restoration and what modifications are needed when working in this subfield.

Transcriptomic and metabolomic analysis of autumn leaf color change in Fraxinus angustifolia

Fraxinus angustifolia is a type of street tree and shade tree with ornamental value. It has a beautiful shape and yellow or reddish purple autumn leaves, but its leaf color formation mechanism and molecular regulation network need to be studied. In this study, we integrated the metabolomes and transcriptomes of stage 1 (green leaf) and stage 2 (red-purple leaf) leaves at two different developmental stages to screen differential candidate genes and metabolites related to leaf color variation. The results of stage 1 and stage 2 transcriptome analysis showed that a total of 5,827 genes were differentially expressed, including 2,249 upregulated genes and 3,578 downregulated genes. Through functional enrichment analysis of differentially expressed genes, we found that they were involved in flavonoid biosynthesis, phenylpropanoid biosynthesis, pigment metabolism, carotene metabolism, terpenoid biosynthesis, secondary metabolite biosynthesis, pigment accumulation, and other biological processes. By measuring the metabolites of Fraxinus angustifolia leaves, we found the metabolites closely related to the differentially expressed genes in two different periods of Fraxinus angustifolia, among which flavonoid compounds were the main differential metabolites. Through transcriptome and metabolomics data association analysis, we screened nine differentially expressed genes related to anthocyanins. Transcriptome and qRT-PCR results showed that these nine genes showed significant expression differences in different stages of the sample, and we speculate that they are likely to be the main regulatory factors in the molecular mechanism of leaf coloration. This is the first time that we have analyzed the transcriptome combination metabolome in the process of leaf coloration of Fraxinus angustifolia, which has important guiding significance for directional breeding of colored-leaf Fraxinus species and will also give new insights for enriching the landscape.

New insight into the microbiome, resistome, and mobilome on the dental waste water in the context of heavy metal environment

Object

Hospital sewage have been associated with incorporation of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) into microbes, which is considered as a key indicator for the spread of antimicrobial resistance (AMR). The compositions of dental waste water (DWW) contain heavy metals, the evolution of AMR and its effects on the water environment in the context of heavy metal environment have not been seriously investigated. Thus, our major aims were to elucidate the evolution of AMR in DWW.

Methods

DWW samples were collected from a major dental department. The presence of microbial communities, ARGs, and MGEs in untreated and treated (by filter membrane and ozone) samples were analyzed using metagenomics and bioinformatic methods.

Results

DWW-associated resistomes included 1,208 types of ARGs, belonging to 29 antibiotic types/subtypes. The most abundant types/subtypes were ARGs of multidrug resistance and of antibiotics that were frequently used in the clinical practice. Pseudomonas putida, Pseudomonas aeruginosa, Chryseobacterium indologenes, Sphingomonas laterariae were the main bacteria which hosted these ARGs. Mobilomes in DWW consisted of 93 MGE subtypes which belonged to 8 MGE types. Transposases were the most frequently detected MGEs which formed networks of communications. For example, ISCrsp1 and tnpA.5/4/11 were the main transposases located in the central hubs of a network. These significant associations between ARGs and MGEs revealed the strong potential of ARGs transmission towards development of antimicrobial-resistant (AMR) bacteria. On the other hand, treatment of DWW using membranes and ozone was only effective in removing minor species of bacteria and types of ARGs and MGEs.

Conclusion

DWW contained abundant ARGs, and MGEs, which contributed to the occurrence and spread of AMR bacteria. Consequently, DWW would seriously increase environmental health concerns which may be different but have been well-documented from hospital waste waters.

Culturable bacteria diversity in stem liquid and resina from Populus euphratica and screening of plant growth-promoting bacteria

BACKGROUND

Populus euphratica Olivier is a kind of tree capable of growing in extremely arid desert and semi-desert environments. In this study, a culture-dependent method was used to analyze the bacterial diversity of stem liquid of P. euphratica and resina of P. euphratica, and to further evaluate plant growth promoting (PGP) activity.

RESULTS

A total of 434 bacteria were isolated from stem fluid and resina of P. euphratica in Ebinur Lake Wetland Nature Reserve and Mulei Primitive forest. The results of taxonomic composition analysis shows that Gammaproteobacteria, Firmicutes, and Actinobacteria_c are the three dominant groups in all the communities, and the representative genera are Bacillus, Nesterenkonia and Halomonas. The diversity analysis shows that the culturable bacterial community diversity of P. euphratica in Ebinur Lake Wetland Nature Reserve is higher than that in Mulei Primitive forest, and the bacterial community diversity of P. euphratica stem fluid is higher than that of resina. According to PGP activity evaluation, 158 functional bacteria with plant growth promoting potential were screened. Among them, 61 strains havephosphorus solubilizing abilities, 80 strains have potassium solubilizing abilities, 32 strains have nitrogen fixation abilities, and 151 strains have iron ammonia salt utilization abilities. The germination rate, plant height, and dry weight of the maize seedlings treated with strains BB33-1, TC10 and RC6 are significantly higher than those of the control group.

CONCLUSION

In this study, a large number of culturable bacteria were isolated from P. euphratica, which provides new functional bacteria sources for promoting plant growth.

Monitoring SARS-CoV-2 Infection Using a Double Reporter-Expressing Virus

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the highly contagious agent responsible for the coronavirus disease 2019 (COVID-19) pandemic. An essential requirement for understanding SARS-CoV-2 biology and the impact of antiviral therapeutics is a robust method to detect the presence of the virus in infected cells or animal models. Despite the development and successful generation of recombinant (r)SARS-CoV-2-expressing fluorescent or luciferase reporter genes, knowledge acquired from their use in in vitro assays and/or in live animals is limited to the properties of the fluorescent or luciferase reporter genes. Herein, for the first time, we engineered a replication-competent rSARS-CoV-2 that expresses both fluorescent (mCherry) and luciferase (Nluc) reporter genes (rSARS-CoV-2/mCherry-Nluc) to overcome limitations associated with the use of a single reporter gene. In cultured cells, rSARS-CoV-2/mCherry-Nluc displayed similar viral fitness as rSARS-CoV-2 expressing single reporter fluorescent and luciferase genes (rSARS-CoV-2/mCherry and rSARS-CoV-2/Nluc, respectively) or wild-type (WT) rSARS-CoV-2, while maintaining comparable expression levels of both reporter genes. In vivo, rSARS-CoV-2/mCherry-Nluc has similar pathogenicity in K18 human angiotensin-converting enzyme 2 (hACE2) transgenic mice than rSARS-CoV-2 expressing individual reporter genes or WT rSARS-CoV-2. Importantly, rSARS-CoV-2/mCherry-Nluc facilitates the assessment of viral infection and transmission in golden Syrian hamsters using in vivo imaging systems (IVIS). Altogether, this study demonstrates the feasibility of using this novel bioreporter-expressing rSARS-CoV-2 for the study of SARS-CoV-2 in vitro and in vivo. IMPORTANCE Despite the availability of vaccines and antivirals, the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to ravage health care institutions worldwide. Previously, we generated replication-competent recombinant (r)SARS-CoV-2 expressing fluorescent or luciferase reporter proteins to track viral infection in vitro and/or in vivo. However, these rSARS-CoV-2 are restricted to express only a single fluorescent or a luciferase reporter gene, limiting or preventing their use in specific in vitro assays and/or in vivo studies. To overcome this limitation, we have engineered a rSARS-CoV-2 expressing both fluorescent (mCherry) and luciferase (Nluc) genes and demonstrated its feasibility to study the biology of SARS-CoV-2 in vitro and/or in vivo, including the identification and characterization of neutralizing antibodies and/or antivirals. Using rodent models, we visualized SARS-CoV-2 infection and transmission through in vivo imaging systems (IVIS).

Identification of Differentially Expressed Intronic Transcripts in Osteosarcoma

Over the past decade; the discovery and characterization of long noncoding RNAs (lncRNAs) have revealed that they play a major role in the development of various diseases; including cancer. Intronic transcripts are one of the most fascinating lncRNAs that are located within intron regions of protein-coding genes, which have the advantage of encoding micropeptides. There have been several studies looking at intronic transcript expression profiles in cancer; but almost none in osteosarcoma. To overcome this problem; we have investigated differentially expressed intronic transcripts between osteosarcoma and normal bone tissues. The results highlighted that NRG1-IT1; FGF14-IT1; and HAO2-IT1 were downregulated; whereas ER3-IT1; SND1-IT1; ANKRD44-IT1; AGAP1-IT1; DIP2A-IT1; LMO7DN-IT1; SLIT2-IT1; RNF216-IT1; and TCF7L1-IT1 were upregulated in osteosarcoma tissues compared to normal bone tissues. Furthermore, we identified if the transcripts encode micropeptides and the transcripts' locations in a cell.

Characterization of Vaginal Microbiota in Third Trimester Premature Rupture of Membranes Patients through 16S rDNA Sequencing

In China, premature rupture of membranes (PROM) counts as a major pregnancy complication in China and usually results into adverse pregnancy outcomes. We analysed the vagina microbiome composition using 16S rDNA V3−V4 amplicon sequencing technology, in this prospective study of 441 women in their third trimester of pregnancy. We first divided all subjects into PROM and HC (healthy control) groups, in order to investigate the correlation of vagina microbiome composition and the development of PROM. We found that seven pathogens were higher in the PROM group as compared to the HC group with statistical significance. We also split all subjects into three groups based on Lactobacillus abundance-dominant (Lactobacillus > 90%), intermediate (Lactobacillus 30−90%) and depleted (Lactobacillus < 30%) groups, and explored nine pathogenic genera that were higher in the depleted group than the intermediate and dominant groups having statistical significance. Finally, using integrated analysis and logistics regression modelling, we discovered that Lactobacillus (coeff = −0.09, p = 0.04) was linked to the decreased risk of PROM, while Gardnerella (coeff = 0.04, p = 0.02), Prevotella (coeff = 0.11, p = 0.02), Megasphaera (coeff = 0.04, p = 0.01), Ureaplasma (coeff = 0.004, p = 0.01) and Dialister (coeff = 0.001, p = 0.04) were associated with the increased risk of PROM. Further study on how these pathogens interact with vaginal microbiota and the host would result in a better understanding of PROM development.

Identification of Potential Pathways of Morella cerifera Seedlings in Response to Alkali Stress via Transcriptomic Analysis

Alkali stress, a type of abiotic stress, severely inhibits plant growth. Only a few studies have investigated the mechanism underlying the transcriptional-level response of Morella cerifera to saline-alkali stress. Based on RNA-seq technology, gene expression differences in the fibrous roots of M. cerifera seedlings exposed to low- and high-concentration alkali stress (LAS and HAS, respectively) were investigated, and the corresponding 1312 and 1532 alkali stress-responsive genes were identified, respectively. According to gene set enrichment analysis, 65 gene sets were significantly enriched. Of these, 24 gene sets were shared by both treatment groups. LAS and HAS treatment groups exhibited 9 (all downregulated) and 32 (23 downregulated) unique gene sets, respectively. The differential gene sets mainly included those involved in trehalose biosynthesis and metabolism, phospholipid translocation, and lignin catabolism. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that M. cerifera seedlings were specifically enriched in stilbenoid, diarylheptanoid, and gingerol biosynthesis; phenylalanine, tyrosine, and tryptophan biosynthesis; and sesquiterpenoid and triterpenoid biosynthesis. Moreover, the related genes involved in hormone signaling pathways and transcription factors were determined through a localization analysis of core abiotic stress pathways. These genes and their molecular mechanisms will be the focus of future research.