Profiling Tools Research Articles

S1-3 Creating Active Schools

Abstract Purpose The Creating Active Schools Framework was co-developed in June 2019 by 50 national and international stakeholders (teachers, headteachers, active school coordinators, Public Health leads, Active Partnership school leads, UK and international researchers, national sport and education organisations, members of the local delivery pilots). The co-developed CAS programme takes a professional development approach to support schools to review current provision and make evidence-informed decisions to address school policy, environments, and stakeholder behaviour to improve opportunities for children to be physically active (https://ijbnpa.biomedcentral.com/articles/10.1186/s12966-020-0917-z). Project description Since conception, the framework has been adopted by practice and has currently scaled to work across 18 localities in England and over 200 schools. As part of this journey, the development of the online profiling tool (https://www.creatingactiveschools.org), a central piece of the intervention approach that places professional development for physical activity at the heart of the school community will be shared. Key learning on drawing partners and stakeholders from across, policy, research and practice together will be provided as well as an overview of the planned wider rollout of CAS (adding a further 20 localities and 200 schools from Sept 2023). Plans for the interdisciplinary evaluation of the implementation of CAS at scale and the cost(effectiveness) of the programme under naturalistic conditions will be provided. Conclusions CAS, the UK’s first large-scale whole school physical activity programme, is uniquely placed to provide much-needed evidence to inform government investment and educational reform on how to scale health-based interventions under real-word conditions.

Implementation of a formalized evaluation and planning tool to improve pediatric oncology outcomes in Kenya.

Survival from pediatric cancers in low middle-income countries is often very low compared to that of high-income countries due to multifactorial etiologies, including late presentation, delayed diagnosis, difficulty with accessing healthcare, drug unavailability, and treatment abandonment. The St. Jude Pediatric Oncology Facility Integrated Local Evaluation Tool (PrOFILE) was developed to map and evaluate childhood cancer healthcare delivery in individual institutions and entire countries, identifying the strengths and weaknesses, as well as opportunities for advancement of care. Using the PrOFILE self-assessment tool, selected Kenyan pediatric oncology facilities entered data into 12 modules: national context, facility and local context, finances and resources, personnel, service capacity, service integration, diagnostics, chemotherapy, supportive care, surgery, radiation therapy, and patients and outcomes. These modules are grouped into five specific components, including Context, Workforce, Diagnostics, Therapy, and Patients and Outcomes. The St. Jude PrOFILE team analyzed the data and organized the first hybrid workshop, containing both in-person and virtual components. Multidisciplinary stakeholders prioritized recommendations for improving care and developed smart objectives to accomplish identified goals over the following 2years. Strengths and weaknesses of conducting a hybrid global workshop were identified. We demonstrated successful use of the PrOFILE tool to conduct a hybrid workshop and identify strategies to improve pediatric oncology care in Kenya. The voluntarily structured work groups will methodically aim to achieve outcome-oriented goals moving forward.

Liquid biopsy comprehensive genomic profiling of lung cancer in the Italian population: A real-world experience

ObjectivesLiquid biopsy with next-generation sequencing (NGS) has emerged as a promising tool for tumor mutation profiling. In this study, we describe the genomic profile of Italian lung cancer patients tested with blood-based comprehensive genomic profiling (CGP) to assess the genomic landscape complexity and its impact on enhancing treatment options for patients. Materials and methodsBetween January 2021 and December 2021, a total of 229 lung cancer patients were profiled by FoundationOne®Liquid CDx (F1LCDx®) assay on circulating tumor DNA (ctDNA). F1LCDx® reports alterations across 324 cancer-related genes and genomic signatures, including tumor fraction (TF) and blood-based tumor mutational burden (bTMB). Detected variants were classified according to the ESMO Scale of Clinical Actionability for molecular Targets (ESCAT). Results90.4% of patients had at least one detectable alteration in plasma. The most frequently mutated genes were TP53 (47.6%), DNMT3A (33.2%), EGFR (20.1%), and KRAS (15.7%). Elevated TF was detected in 18.3% of patients, suggesting high reliability of test results. According to the ESCAT classification, potentially actionable alterations (Tier I-II) were identified in 27.1% of samples. An additional 5.2% harbored an alteration for which an approved drug is available in other cancer types (Tier III). Furthermore, 13.1% of tumors exhibited high bTMB, which may predict response to immunotherapy. Overall, 156 (68.1%) patients were eligible for enrolment in clinical trials. ConclusionLiquid biopsy NGS is a viable and valuable approach to guide personalized therapy. The use of blood-based CGP may help identify a larger number of actionable mutations and increase chances of enrolment in clinical trials.

Challenges and insights in the exploration of the low abundance human ocular surface microbiome.

The low microbial abundance on the ocular surface results in challenges in the characterization of its microbiome. The purpose of this study was to reveal factors introducing bias in the pipeline from sample collection to data analysis of low-abundant microbiomes. Lower conjunctiva and lower lid swabs were collected from six participants using either standard cotton or flocked nylon swabs. Microbial DNA was isolated with two different kits (with or without prior host DNA depletion and mechanical lysis), followed by whole-metagenome shotgun sequencing with a high sequencing depth set at 60 million reads per sample. The relative microbial compositions were generated using the two different tools MetaPhlan3 and Kraken2. The total amount of extracted DNA was increased by using nylon flocked swabs on the lower conjunctiva. In total, 269 microbial species were detected. The most abundant bacterial phyla were Actinobacteria, Firmicutes and Proteobacteria. Depending on the DNA extraction kit and tool used for profiling, the microbial composition and the relative abundance of viruses varied. The microbial composition on the ocular surface is not dependent on the swab type, but on the DNA extraction method and profiling tool. These factors have to be considered in further studies about the ocular surface microbiome and other sparsely colonized microbiomes in order to improve data reproducibility. Understanding challenges and biases in the characterization of the ocular surface microbiome may set the basis for microbiome-altering interventions for treatment of ocular surface associated diseases.

Abstract 051: Racial Differences In Hypertension Self-care Behaviors Among Adults With Hypertension In The Baltimore And Washington, D.C. Area

Introduction: Interventions utilizing comprehensive hypertension (HBP) self-care evaluation tools may reduce HBP disparities. However, studies examining racial differences in HBP self-care among people diagnosed with HBP are limited. Methods: We analyzed cross-sectional data from adults with HBP that receive care in the Baltimore and Washington D.C. area. Twenty self-care behaviors were examined via the Hypertension Self-Care Profile (HBP-SCP) tool and scored as 4-point Likert with total scores ranging between 20-80. Multinomial logistic regression models were used to assess the association between race categories (White, Black/African American, Asian, American Indian/Alaskan Native, Native Hawaiian/Pacific Islander, Other/Multi-racial) and HBP-SCP behaviors, adjusting for covariates. Results: The study included 4,391 adults diagnosed with HBP (mean age 62 ± 12 years; 55% female). The median HBP-SCP score was 47 and scores ≥ 47 or <47 were rated as good and poor, HBP self-care behavior, respectively. Compared to White adults, Asian and Black/African American adults were 29% less likely and 21% more likely, respectively, to have good HBP self-care behavior in the unadjusted model. Asian and Other/Multi-racial adults were 38% and 35%, respectively, less likely to have good HBP self-care behavior after adjusting for covariates compared to White adults (Table 1). Conclusion: Racial differences exist in HBP self-care behaviors among adults with HBP. These findings highlight the importance of practitioners assessing patients’ understanding of and adherence to self-care behaviors and developing culturally tailored approaches for improving adherence.

Metagenomic profiling pipelines improve taxonomic classification for 16S amplicon sequencing data

Most experiments studying bacterial microbiomes rely on the PCR amplification of all or part of the gene for the 16S rRNA subunit, which serves as a biomarker for identifying and quantifying the various taxa present in a microbiome sample. Several computational methods exist for analyzing 16S amplicon sequencing. However, the most-used bioinformatics tools cannot produce high quality genus-level or species-level taxonomic calls and may underestimate the potential accuracy of these calls. We used 16S sequencing data from mock bacterial communities to evaluate the sensitivity and specificity of several bioinformatics pipelines and genomic reference libraries used for microbiome analyses, concentrating on measuring the accuracy of species-level taxonomic assignments of 16S amplicon reads. We evaluated the tools DADA2, QIIME 2, Mothur, PathoScope 2, and Kraken 2 in conjunction with reference libraries from Greengenes, SILVA, Kraken 2, and RefSeq. Profiling tools were compared using publicly available mock community data from several sources, comprising 136 samples with varied species richness and evenness, several different amplified regions within the 16S rRNA gene, and both DNA spike-ins and cDNA from collections of plated cells. PathoScope 2 and Kraken 2, both tools designed for whole-genome metagenomics, outperformed DADA2, QIIME 2 using the DADA2 plugin, and Mothur, which are theoretically specialized for 16S analyses. Evaluations of reference libraries identified the SILVA and RefSeq/Kraken 2 Standard libraries as superior in accuracy compared to Greengenes. These findings support PathoScope and Kraken 2 as fully capable, competitive options for genus- and species-level 16S amplicon sequencing data analysis, whole genome sequencing, and metagenomics data tools.

Droplet-based high-throughput single microbe RNA sequencing by smRandom-seq

Bacteria colonize almost all parts of the human body and can differ significantly. However, the population level transcriptomics measurements can only describe the average bacteria population behaviors, ignoring the heterogeneity among bacteria. Here, we report a droplet-based high-throughput single-microbe RNA-seq assay (smRandom-seq), using random primers for in situ cDNA generation, droplets for single-microbe barcoding, and CRISPR-based rRNA depletion for mRNA enrichment. smRandom-seq showed a high species specificity (99%), a minor doublet rate (1.6%), a reduced rRNA percentage (32%), and a sensitive gene detection (a median of ~1000 genes per single E. coli). Furthermore, smRandom-seq successfully captured transcriptome changes of thousands of individual E. coli and discovered a few antibiotic resistant subpopulations displaying distinct gene expression patterns of SOS response and metabolic pathways in E. coli population upon antibiotic stress. smRandom-seq provides a high-throughput single-microbe transcriptome profiling tool that will facilitate future discoveries in microbial resistance, persistence, microbe-host interaction, and microbiome research.

StrainIQ: A Novel n-Gram-Based Method for Taxonomic Profiling of Human Microbiota at the Strain Level.

The emergence of next-generation sequencing (NGS) technology has greatly influenced microbiome research and led to the development of novel bioinformatics tools to deeply analyze metagenomics datasets. Identifying strain-level variations in microbial communities is important to understanding the onset and progression of diseases, host-pathogen interrelationships, and drug resistance, in addition to designing new therapeutic regimens. In this study, we developed a novel tool called StrainIQ (strain identification and quantification) based on a new n-gram-based (series of n number of adjacent nucleotides in the DNA sequence) algorithm for predicting and quantifying strain-level taxa from whole-genome metagenomic sequencing data. We thoroughly evaluated our method using simulated and mock metagenomic datasets and compared its performance with existing methods. On average, it showed 85.8% sensitivity and 78.2% specificity on simulated datasets. It also showed higher specificity and sensitivity using n-gram models built from reduced reference genomes and on models with lower coverage sequencing data. It outperforms alternative approaches in genus- and strain-level prediction and strain abundance estimation. Overall, the results show that StrainIQ achieves high accuracy by implementing customized model-building and is an efficient tool for site-specific microbial community profiling.

Stroke Risk, Practice and Health Promotion Guidance among Geriatric Patients: Randomized Control Trail

Background: Stroke is one of the world’s chief reasons of death and infirmity among geriatric. Objective: The research at hand analyzed the association among the rFSRP and health promotion lifestyle and practice about stroke prevention among geriatric patients. Design: A randomized controlled experimental study was used in this study. This study included 85 study and 85 control participants. Methods: Participants were randomly selected and provided with an educational intervention on health-promoting lifestyle behaviors. Data were collected via Tool (I): demographic and clinical data of geriatric patients, Tool (II): Revised Framingham Stroke Risk Profile (R- FSRP) Tool (III): geriatric patients’ practices about stroke prevention, and Tool IV: Health Promoting Lifestyle Profile II (HPLP II) pre, and three months after the program intervention. Results: The data analysis revealed noteworthy dissimilarities between the experimental and control groups, which were deemed statistically significant and pre and follow - up intervention regarding (R- FSRP), practice and health promotion (p < 0.05.). Conclusion:The study concluded that the intervention program had a positive effect on stroke risk, practices and health promotion lifestyle.

Photoreactive Probe-Based Strategy Enables the Specific Identification of the Transient Substrates of Methyltransferase at the Proteome Scale.

To decipher the biological function of protein arginine methyltransferases (PRMTs), the identification of their substrate proteins is crucial. However, this is not a trivial task as the stable and strong interacting proteins always prevail over the weak and transient substrate proteins. Herein, we report the development of a novel photoreactive probe-based strategy to identify the substrate proteins of methyltransferases. By applying it to PRMT1, we demonstrate that this strategy can effectively distinguish substrate proteins from other interacting proteins and allows the identification of highly confident substrate proteins. Noteworthily, we found for the first time that hypomethylation of proteins is a prerequisite for efficient capturing of substrate proteins. This study describes the development of a robust chemical proteomics tool for profiling the transient substrates and can be adapted for broad biomedical applications.

Genetic Predictors of Comorbid Course of COVID-19 and MAFLD: A Comprehensive Analysis.

Metabolic-associated fatty liver disease (MAFLD) and its potential impact on the severity of COVID-19 have gained significant attention during the pandemic. This review aimed to explore the genetic determinants associated with MAFLD, previously recognized as non-alcoholic fatty liver disease (NAFLD), and their potential influence on COVID-19 outcomes. Various genetic polymorphisms, including PNPLA3 (rs738409), GCKR (rs780094), TM6SF2 (rs58542926), and LYPLAL1 (rs12137855), have been investigated in relation to MAFLD susceptibility and progression. Genome-wide association studies and meta-analyses have revealed associations between these genetic variants and MAFLD risk, as well as their effects on lipid metabolism, glucose regulation, and liver function. Furthermore, emerging evidence suggests a possible connection between these MAFLD-associated polymorphisms and the severity of COVID-19. Studies exploring the association between indicated genetic variants and COVID-19 outcomes have shown conflicting results. Some studies observed a potential protective effect of certain variants against severe COVID-19, while others reported no significant associations. This review highlights the importance of understanding the genetic determinants of MAFLD and its potential implications for COVID-19 outcomes. Further research is needed to elucidate the precise mechanisms linking these genetic variants to disease severity and to develop gene profiling tools for the early prediction of COVID-19 outcomes. If confirmed as determinants of disease severity, these genetic polymorphisms could aid in the identification of high-risk individuals and in improving the management of COVID-19.

TTProfiler: Types and Terms Profile Building for Online Cultural Heritage Knowledge Graphs

As more and more knowledge graphs (KGs) are published on the Web, there is a need for tools that show their content. This implies showing the schema-level patterns instantiated in the graph, but also the terms used to qualify its entities. In this article, we present a new profiling tool that we call TTprofiler. It shows the predicates that relate types in the KG, and also the terms present in this KG, because of their paramount importance in most KGs, especially in the Cultural Heritage (CH) domain. We recall the role of terminologies and how they are implemented and used on the Web, we give the algorithm for building a TT profile from an online KG’s endpoint, and we report on experiments performed over a set of Cultural Heritage Web KGs. A tool for visualizing TT profiles is also provided.

Circulating Tumor DNA in Head and Neck Squamous Cell Carcinoma: Association with Metabolic Tumor Burden Determined with FDG-PET/CT.

The detection of circulating tumor DNA (ctDNA) with next-generation sequencing (NGS) in venous blood is a promising tool for the genomic profiling of head and neck squamous cell carcinoma (HNSCC). The association between ctDNA findings and metabolic tumor burden detected with FDG-PET/CT imaging is of particular interest for developing prognostic and predictive algorithms in HNSCC. Twenty-six prospectively enrolled HNSCC patients were eligible for further analysis. All patients underwent tumor tissue and venous liquid biopsy sampling and FDG-PET/CT before definitive oncologic treatment. An NGS-based commercial panel was used for a genomic analysis of the samples. Maximum variant allele frequency (VAF) in blood correlated positively with whole-body (WB) metabolic tumor volume (MTV) and total lesion glycolysis (TLG) (r = 0.510, p = 0.008 and r = 0.584, p = 0.002, respectively). A positive liquid biopsy was associated with high WB-TLG using VAF ≥ 1.00% or ≥5.00% as a cut-off value (p = 0.006 or p = 0.003, respectively). Additionally, ctDNA detection was associated with WB-TLG when only concordant variants detected in both ctDNA and tissue samples were considered. A high metabolic tumor burden based on FDG imaging is associated with a positive liquid biopsy and high maximum VAF. Our findings suggest a complementary role of metabolic and genomic signatures in the pre-treatment evaluation of HNSCC.

Assessing Contaminant Mass Discharge Uncertainty With Application of Hydraulic Conductivities Derived From Geoelectrical Cross‐Borehole Induced Polarization and Other Methods

AbstractA new methodology was developed to support contaminant mass discharge (CMD)‐based risk assessment of groundwater contamination downgradient of point source zones. Geoelectrical cross‐borehole induced polarization (IP) data were collected at a site undergoing in situ remediation of chlorinated solvents for determining 2D hydraulic conductivity (K) distributions with an inversion model resolution of 0.15 m (vertically) x 0.50 m (horizontally) in three control planes from 10 to 20 m depth. Additionally, 18 slug tests and 31 grain size distribution analyses (GSA) from the control planes, were used for K‐estimation. The geometric means and variance of the IP, slug test, and GSA derived K‐estimates were consistent with previously studied sandy aquifers. Furthermore, the vertical variation in K between two geological settings, a sandy till and a meltwater sand formation, was clearly identified by the IP K‐estimates. The vertical variation was backed up by hydraulic profiling tool (HPT) measurements. Random realizations of CMD were simulated based on the cross‐borehole IP derived K‐values. For comparison, the CMD was also estimated with a geostatistical conditional simulation approach, using the data from slug tests and GSAs. The high IP resolution captured the small scale variations in K across the transects and led to CMD predictions with a narrow uncertainty interval, whereas slug test and GSA either under‐ or overestimated the magnitude of the areas with the highest CMD. Applying the geophysical cross‐borehole method for estimating K‐distributions in addition to traditional methods would improve CMD‐based risk assessment and evaluation of remediation performance at contaminated sites.

Evaluating the efficacy of the Thai Health Improvement Profile intervention for preventing weight gain in people with early stage psychosis: A randomized controlled trial

ObjectivesTo investigate the efficacy of the Thai Health Improvement Profile intervention for preventing clinically significant weight gain in people with early stage psychosis. MethodsWe undertook a randomised controlled trial from 10/2018 to 05/2021. Participants with early stage psychosis (<5 year duration) were recruited using convenience sampling from the caseloads of community psychiatric nurses in Thailand and randomly allocated to either the Thai Health Improvement Profile intervention or treatment as usual group following baseline assessment. Outcome assessors were blind to group allocation, whereas participants were not. Participants in the intervention group received three monthly (five in total) systematic health checks using the Thai Health Improvement Profile tool, which was used to develop a personal health plan in collaboration with a family member/carer. Nurses supported participants to implement the health plan using behaviour change techniques derived from motivational interviewing. The treatment as usual group consisted of medication and psychosocial support, and no additional intervention was provided. The primary outcome was weight gain (defined as a greater or equal to 7 % increase in weight against baseline) within 1 year. ResultsFifty-three participants were allocated to the intervention and an equal number to the treatment as usual group. Primary outcome data were available for 30 participants in each group at the 12 month follow-up. We undertook an intention to treat analysis with multiple imputation (to handle the missing data) for the primary outcome. The treatment as usual group was found to have higher odds than the Thai Health Improvement Profile intervention group of gaining ≥7 % of baseline body weight (OR = 6.52; 95 % CI: 1.88–22.65, p = 0.004). ConclusionsThe Thai Health Improvement Profile intervention was effective at preventing weight gain in people with early stage psychosis at one year, though attrition was relatively high. The results highlight the need for community mental health nurses to adopt a holistic approach, the potential benefits of conducting regular comprehensive health checks and the importance of involving family members when aiming to improve the physical health of people diagnosed with early stage psychosis. A large definitive multi-site randomised controlled trial of the Thai Health Improvement Profile with a longer follow-up is now justified. Trial registrationProspectively registered with the Thai Clinical Trials Registry (reference: TCTR20180305002).

Diversity of Streptococcus spp. and genomic characteristics of Streptococcus uberis isolated from clinical mastitis of cattle in Bangladesh.

Streptococci are the major etiology in mastitis in dairy cattle, a cause of huge economic losses in the dairy industries. This study was aimed to determine the diversity of Streptococcus spp. isolated from clinical mastitis of cattle reared in Bangladesh. A total of 843 lactating cattle reared in four prominent dairy farms and one dairy community were purposively included in this study where 80 cattle were positive to clinical mastitis (CM) based on gross changes in the udder (redness, swelling, and sensitive udder) and/or milk (flakes and/or clots). Milk samples were collected from all the eighty cattle with clinical mastitis (CCM) and twenty five apparently healthy cattle (AHC). Samples were enriched in Luria Bertani broth (LB) and one hundred microliter of the enrichment culture was spread onto selective media for the isolation of Staphylococcus spp., Streptococcus spp., Enterococcus spp., Escherichia coli and Corynebacterium spp., the major pathogen associated with mastitis. Isolates recovered from culture were further confirmed by species specific PCR. Out of 105 samples examined 56.2% (59/105), 17.14% (18/105), 9.52% (10/105) and 22.9% (24/105) samples were positive for Staphylococcus, Streptococcus, Enterococcus faecalis and E. coli, respectively. This study was then directed to the determination of diversity of Streptococcus spp. through the sequencing of 16S rRNA. A total of eighteen of the samples from CCM (22.5%) but none from the AHC were positive for Streptococcus spp. by cultural and molecular examination. Sequencing and phylogenetic analysis of 16S rRNA identified 55.6, 33.3, 5.6 and 5.6% of the Streptococcus isolates as Streptococcus uberis, Streptococcus agalactiae, Streptococcus hyovaginalis and Streptococcus urinalis, respectively. Considering the high prevalence and worldwide increasing trend of S. uberis in mastitis, in-depth molecular characterization of S. uberis was performed through whole genome sequencing. Five of the S. uberis strain isolated in this study were subjected to WGS and on analysis two novel ST types of S. uberis were identified, indicating the presence of at least two different genotypes of S. uberis in the study areas. On virulence profiling, all the isolates harbored at least 35 virulence and putative virulence genes probably associated with intramammary infection (IMI) indicating all the S. uberis isolated in this study are potential mastitis pathogen. Overall findings suggest that Streptococcus encountered in bovine mastitis is diverse and S. uberis might be predominantly associated with CM in the study areas. The S. uberis genome carries an array of putative virulence factors that need to be investigated genotypically and phenotypically to identify a specific trait governing the virulence and fitness of this bacterium. Moreover, the genomic information could be used for the development of new genomic tools for virulence gene profiling of S. uberis.

The legal concept of discrimination by association: where does it fit into the digital era?

Personal autonomy, a core human rights principle, refers to the ability to both design and conduct the course of one’s life through making choices from a range of valuable options. This plays a pivotal role in the realm of equality and non discrimination, which are relevant in the context of the European Union (EU). Through case law, the concept of discrimination by association has emerged as a crucial step in strengthening anti-discrimination, recognising that individuals who are not part of a protected group but who have a relationship with someone who is, or are in some way associated with them, may be treated unfavourably, thus requiring appropriate remedies. Currently, the field of non-discrimination increasingly warrants attention, due to the rapid advancement of technology, which harbours unique discriminatory potential. For instance, through data mining and the use of artificial intelligence tools for profiling and clustering, people may be grouped based on collective characteristics that may not accurately represent their individual features, resulting in differential treatment regardless of whether legally recognised vulnerable groups are involved. It therefore becomes crucial to question to what extent discrimination by association can effectively address this discriminatory power or whether new measures need to be developed to safeguard personal autonomy and prevent the proliferation of such phenomena in the current digital landscape.

Keystroke Dynamics as a Language Profiling Tool: Identifying Mother Tongue of Unknown Internet Users

Understanding the distinct characteristics of unidentified Internet users is helpful in various contexts, including digital forensics, targeted advertising, and user interaction with services and systems. Keystroke dynamics (KD) enables the analysis of data derived from a user’s typing behaviour on a keyboard as one approach to obtain such information. This study conducted experiments on a developed dataset that recorded samples of typing in five different mother tongues to determine Internet users’ mother tongue. Based on only a few KD features and machine learning techniques, 82% accuracy was achieved in recognising an unknown user’s mother tongue. This research highlights the potential for KD as a reliable method for identifying the mother tongue of Internet users, with implications for various applications such as improving digital forensic investigations, targeted advertising strategies, and optimising user experiences with online services.

Transcriptome analysis provides insights into the stress response in cultivated peanut (Arachis hypogaea L.) subjected to drought-stress.

Peanut (Arachis hypogaea L.) is one of the valuable oilseed crops grown in drought-prone areas worldwide. Drought severely limits peanut production and productivity significantly. In order to decipher the drought tolerance mechanism in peanut under drought stress, RNA sequencing was performed in TAG - 24 (drought tolerant genotype) and JL-24 (drought susceptible genotype). Approximately 51million raw reads were generated from four different libraries of two genotypes subjected to drought stress exerted by 20% PEG 6000 stress and control conditions, of which ~ 41million (80.87%) filtered reads were mapped to the Arachis hypogaea L. reference genome. The transcriptome analysis detected 1,629 differentially expressed genes (DEGs), 186 genes encoding transcription factors (TFs) and 30,199 SSR among the identified DEGs. Among the differentially expressed TF encoding genes, the highest number of genes were WRKY followed by bZIP, C2H2, and MYB during drought stress. The comparative analysis between the two genotypes revealed that TAG-24 exhibits activation of certain key genes and transcriptional factors that are involved in essential biological processes. Specifically, TAG-24 showed activation of genes involved in the plant hormone signaling pathway such as PYL9, Auxin response receptor gene, and ABA. Additionally, genes related to water deprivation such as LEA protein and those involved in combating oxidative damage such as Glutathione reductase were also found to be activated in TAG-24. This genome-wide transcription map, therefore, provides a valuable tool for future transcript profiling under drought stress and enriches the genetic resources available for this important oilseed crop.

From waste to resource: Metagenomics uncovers the molecular ecological resources for plastic degradation in estuaries of South China

Estuaries are hotspots of plastic pollution due to accumulated waste from surrounding rivers and coasts. However, the molecular ecological resources that possess plastic-degrading traits and their biogeographic distributions in estuarine waters remain to be elucidated. In this study, we mapped the distribution profiles of plastic-degrading genes (PDGs) in 30 subtropical estuaries in China based on metagenomic sequencing. A total of 41 PDG subtypes were observed in these estuaries. The Pearl River Estuary had higher diversity and abundance of PDGs than the east and west region estuaries. Genes for degrading synthetic heterochain and natural plastics were the most diverse and abundant types, respectively. The abundance of synthetic PDGs was significantly higher in estuaries affected by intense anthropogenic activities. Further binning strategies revealed diverse microbes with plastic-degrading ability in these estuaries. Rhodobacteraceae, a dominant plastic-degrading bacterial family, primarily carried PDGs for degrading natural plastics. Pseudomonas veronii carrying diverse PDGs was identified, which may be of value for further technical improvement of plastic degradation. In addition, phylogenetic and structural analyses of 19 putative 3HV dehydrogenases, the most diverse and abundant DPGs, showed inconsistent evolution with their hosts, but different sequences were conserved with consistent key functional amino acids. A potential biodegradation pathway for polyhydroxybutyrate by Rhodobacteraceae was proposed. The result implied that plastic-degrading functions are widely distributed in estuarine waters and metagenomics could be used as a promising screening tool for large-scale profiling of plastic-degrading potential in the natural environment. Our findings have important implications and provide potential molecular ecological resources for developing plastic waste removal technologies.