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This study developed machine learning models using a dataset consisting of 963 entries with 24 variables both numerical and categorical to predict H2 production of plastic waste and biomass gasification. The models were utilized to optimize feedstock and process conditions through genetic algorithm to maximize hydrogen production.
This is the seminar I will present at WCCM conference highlighting our latest research work on incorporating genetic programming to obtain data-driven strength models for complex materials.
Here we provide the complete set of circular elements produced by SCAPP from metagenomic data that may represent mobile genetic elements (MGEs). For the publication, these sequences were de-replicated within the high [U] and low [U] sample sets. Additionally, 98 of the circular elements were removed for downstream analysis due to high suspicion of being (1) chloroplast or mitochondrial sequences or (2) erroneously circularized long repeat regions. The complete list of circular elements used for the analysis along with metadata can be found in Tables S5 and S6.
The image dataset consists of 11,791 images representing 1,219 genotypes of Populus trichocarpa undergoing in planta regeneration. Genotypes were imaged with a median of four weekly timepoints and a median of two replicates each. A representative and diverse subset of 249 images was annotated using the IDEAS annotation interface (ideas.eecs.oregonstate.edu) and these annotated images were used to train a deep semantic segmentation model (PSPNet), which was deployed for inference over the entire dataset. Annotated classes include specific stages of regeneration (callus and shoot) in addition to unregenerated plant material and background. Statistics of relative tissue area were extracted and used for downstream genetic association mapping in a genome-wide association study. The SNP dataset consists of over 40 million single-nucleotide polymorphisms across 1,323 wild accessions of Populus trichocarpa
Plants respond to abiotic stresses such as drought, heat, and salinity through both shared and stress-specific regulatory pathways. However, the role of epigenetic mechanisms, particularly DNA methylation, in modulating these responses is still underexplored. Here, we integrated transcriptome profiling with whole-genome bisulfite sequencing (WGBS) to investigate the dynamic relationship between gene expression and DNA methylation in Populus trichocarpa during brief early-stage exposure to abiotic stress. Each stress elicited distinct transcriptional and methylation signatures; however, a subset of conserved stress-responsive genes was commonly regulated across treatments. Approximately 5% of differentially expressed genes also displayed differential methylation patterns, suggesting a coordinated role for DNA methylation in regulating gene expression. Motif enrichment analysis of differentially methylated regions revealed binding sites of key transcription factor families, including ERF, bHLH, and ABF, highlighting potential role for methylation in modulating transcription factor targeting. Furthermore, we identified stress-inducible molecular markers with potential applications in early stress detection and functional dissection of gene regulatory pathways. Together, these findings provide new insights into the coordinated genetic and epigenetic responses to abiotic stress and provide a foundation for developing biosensors and breeding strategies to enhance stress resilience woody plants.
Experimental Data for Comparison of microbial strains as candidate hosts and genetic reservoirs for the valorization of lignin streams
Nitrate is an inhibitor of sulfate-reducing bacteria (SRB). In petroleum production sites, amendments of nitrate and nitrite are used to prevent SRB production of sulfide that causes souring of oil wells. A better understanding of nitrate stress responses in the model SRB, Desulfovibrio vulgaris Hildenborough and Desulfovibrio alaskensis G20, will strengthen predictions of environmental outcomes of nitrate application. Nitrate inhibition of SRB has historically been considered to result from the generation of small amounts of nitrite, to which SRB are quite sensitive. Here we explored the possibility that nitrate might inhibit SRB by a mechanism other than through nitrite inhibition. We found that nitrate-stressed D. vulgaris cultures grown in lactate-sulfate conditions eventually grew in the presence of high concentrations of nitrate, and their resistance continued through several subcultures. Nitrate consumption was not detected over the course of the experiment, suggesting adaptation to nitrate. With high-throughput genetic approaches employing TnLE-seq for D. vulgaris and a pooled mutant library of D. alaskensis, we determined the fitness of many transposon mutants of both organisms in nitrate stress conditions. We found that several mutants, including homologs present in both strains, had a greatly increased ability to grow in the presence of nitrate but not nitrite. The mutated genes conferring nitrate resistance included the gene encoding the putative Rex transcriptional regulator (DVU0916/Dde_2702), as well as a cluster of genes (DVU0251-DVU0245/Dde_0597-Dde_0605) that is poorly annotated. Follow-up studies with individual D. vulgaris transposon and deletion mutants confirmed high-throughput results. We conclude that, in D. vulgaris and D. alaskensis, nitrate resistance in wild-type cultures is likely conferred by spontaneous mutations. Furthermore, the mechanisms that confer nitrate resistance may be different from those that confer nitrite resistance.
Virginia is the third largest producer of fresh-market tomatoes in the United States. Tomatoes grown along the eastern shore of Virginia are implicated almost yearly in Salmonella illnesses. Traceback implicates contamination occurring in the pre-harvest environment. To get a better understanding of the ecological niches of Salmonella in the tomato agricultural environment, a 2-year study was undertaken at a regional agricultural research farm in Virginia. Environmental samples, including tomato (fruit, blossoms, and leaves), irrigation water, surface water and sediment, were collected over the growing season. These samples were analyzed for the presence of Salmonella using modified FDA-BAM methods. Molecular assays were used to screen the samples. Over 1500 samples were tested. Seventy-five samples tested positive for Salmonella yielding over 230 isolates. The most commonly isolated serovars were S. Newport and S. Javiana with pulsed-field gel electrophoresis yielding 39 different patterns. Genetic diversity was further underscored among many other serotypes, which showed multiple PFGE subtypes. Whole genome sequencing (WGS) of several S. Newport isolates collected in 2010 compared to clinical isolates associated with tomato consumption showed very few single nucleotide differences between environmental isolates and clinical isolates suggesting a source link to Salmonella contaminated tomatoes. Nearly all isolates collected during two growing seasons of surveillance were obtained from surface water and sediment sources pointing to these sites as long-term reservoirs for persistent and endemic contamination of this environment.
Little is known about the underlying basis of serotype specificity among strains of Flavobacterium psychrophilum , the agent of rainbow trout fry syndrome and bacterial cold-water disease. The identification of different heat-stable O-serotypes among strains of this gram-negative pathogen does, however, suggest structural variations in the O-polysaccharide (O-PS) moiety of cell surface lipopolysaccharide (LPS). A trisaccharide composed of L-rhamnose (L-Rha), 2-acetamido-2-deoxy-L-fucose (L-FucNAc) and 2-acetamido-4-R-2,4-dideoxy-D-quinovose (D-Qui2NAc4NR), where R represents a dihydroxyhexanamido derivative, was previously identified as the repeating unit of Fp CSF259-93 O-PS. Interestingly, the O-PS gene cluster of this strain and that of Fp 950106-1/1, which belongs to a different O-serotype, are identical except for wzy, which encodes the putative polymerase that links trisaccharide repeats into O-PS chains. We have now found from results of glycosyl composition analysis and high-resolution nuclear magnetic resonance, that the linkage of D-Qui2NAc4NR to L-Rha, which is α1-2 for Fp CSF259-93 versus β1-3 for Fp 950106-1/1, is the only structural difference between O-PS from these strains. The corresponding difference in O-serotype specificity was established from the reactions of rabbit and trout anti-F. psychrophilum antibody with purified O-PS and LPS. Moreover, LPS-based differences in antigenicity were noted between strains with O-PS loci identical to those of Fp CSF259-93 or Fp 950106-1/1, except for the genes predicted to direct synthesis of different R-groups in Qui2NAc4NR. The findings provide a framework for defining the genetic basis of O-PS structure and antigenicity and suggest that the repertoire of F. psychrophilum O-serotypes extends beyond what is presently recognized from serological studies of this important fish pathogen.
Methylthiotransferases (MTTases) are radical S-adenosylmethionine (SAM) enzymes that catalyze the addition of a methylthio (-SCH 3 ) group to an unreactive carbon center. These enzymes are responsible for the production of 2-methylthioadenosine (ms 2 A) derivatives found at position A37 of select tRNAs in all domains of life. Additionally, some bacteria contain the RimO MTTase that catalyzes the methylthiolation of the S12 ribosomal protein. Although the functions of MTTases in bacteria and eukaryotes have been established via detailed genetic and biochemical studies, MTTases from the archaeal domain of life are understudied and the substrate specificity determinants of MTTases remain unclear. Here, we report the in vitro enzymatic activities of an MTTase (C4B56_06395) from a thermophilic Ca. Methanophagales anaerobic methanotroph (ANME) as well as the MTTase from a hyperthermophilic methanogen – MJ0867 from Methanocaldococcus jannaschii. Both enzymes catalyze the methylthiolation of N 6 -threonylcarbamoyladenosine (t 6 A) and N 6 -hydroxynorvalylcarbamoyladenosine (hn 6 A) residues to produce 2-methylthio-N 6 -threonylcarbamoyladenosine (ms 2 t 6 A) and 2-methylthio-N 6 -hydroxynorvalylcarbamoyladenosine (ms 2 hn 6 A), respectively. To further assess the function of archaeal MTTases, we analyzed select tRNA modifications in a model methanogen – Methanosarcina acetivorans – and generated a deletion of the MTTase-encoding gene (MA1153). We found that M. acetivorans produces ms 2 hn 6 A in exponential phase of growth, but does not produce ms 2 t 6 A in detectable amounts. Upon deletion of MA1153, the ms 2 A modification was absent, thus confirming the function of MtaB-family MTTases in generating ms 2 hn 6 A modified nucleosides in select tRNAs.
Identifying the cell wall-ionically bound glycoside hydrolases (GHs) in Arabidopsis stems is important for understanding the regulation of cell wall integrity. For cell wall proteomics studies, the preparation of clean cell wall fractions is a challenge since cell walls constitute an open compartment, which is more likely to contain a mixture of intracellular and extracellular proteins due to cell leakage at the late growth stage. Here, for this study, we utilize a CaCl 2 -extraction procedure to isolate non-structural proteins from Arabidopsis whole stems, followed by the in-solution and in-gel digestion methods coupled with Nano-LC-MS/MS, bioinformatics and literature analyses. This has led to the identification of 75 proteins identified using the in-solution method and 236 proteins identified by the in-gel method, among which about 10% of proteins predicted to be secreted. Together, eight cell wall proteins, namely AT1G75040, AT5G26000, AT3G57260, AT4G21650, AT3G52960, AT3G49120, AT5G49360, and AT3G14067, were identified by the in-solution method; among them, three were the GHs (AT5G26000, myrosinase 1, GH1; AT3G57260, β-1,3-glucanase 2, GH17; AT5G49360, bifunctional XYL 1/α-L-arabinofuranosidase, GH3). Moreover, four more GHs: AT4G30270 (xyloglucan endotransferase, GH16), AT1G68560 (bifunctional α-l-arabinofuranosidase/XYL, GH31), AT1G12240 (invertase, GH32) and AT2G28470 (β-galactosidase 8, GH35), were identified by the in-gel solution method only. Notably, more than half of above identified GHs are xylan- or hemicellulose-modifying enzymes, and will likely have an impact on cellulose accessibility, which is a critical factor for downstream enzymatic hydrolysis of plant tissues for biofuels production. Finally, the implications of these cell wall proteins identified at the late growth stage for the genetic engineering of bioenergy crops are discussed.
MaizeMine is the data mining resource of the Maize Genetics and Genome Database (MaizeGDB; http://maizemine.maizegdb.org). It enables researchers to create and export customized annotation datasets that can be merged with their own research data for use in downstream analyses. MaizeMine uses the InterMine data warehousing system to integrate genomic sequences and gene annotations from the Zea mays B73 RefGen_v3 and B73 RefGen_v4 genome assemblies, Gene Ontology annotations, single nucleotide polymorphisms, protein annotations, homologs, pathways, and precomputed gene expression levels based on RNA-seq data from the Z. mays B73 Gene Expression Atlas. MaizeMine also provides database cross references between genes of alternative gene sets from Gramene and NCBI RefSeq. MaizeMine includes several search tools, including a keyword search, built-in template queries with intuitive search menus, and a QueryBuilder tool for creating custom queries. The Genomic Regions search tool executes queries based on lists of genome coordinates, and supports both the B73 RefGen_v3 and B73 RefGen_v4 assemblies. The List tool allows you to upload identifiers to create custom lists, perform set operations such as unions and intersections, and execute template queries with lists. When used with gene identifiers, the List tool automatically provides gene set enrichment for Gene Ontology (GO) and pathways, with a choice of statistical parameters and background gene sets. With the ability to save query outputs as lists that can be input to new queries, MaizeMine provides limitless possibilities for data integration and meta-analysis.
The precise role of KNAT7 transcription factors (TFs) in regulating secondary cell wall (SCW) biosynthesis in poplars has remained unknown, while our understanding of KNAT7 functions in other plants is continuously evolving. To study the impact of genetic modifications of homologous and heterologous KNAT7 gene expression on SCW formation in transgenic poplars, we prepared poplar KNAT7 ( PtKNAT7 ) overexpression ( PtKNAT7 -OE) and antisense suppression ( PtKNAT7 -AS) vector constructs for the generation of transgenic poplar lines via Agrobacterium -mediated transformation. Since the overexpression of homologous genes can sometimes result in co-suppression, we also overexpressed Arabidopsis KNAT7 ( AtKNAT7-OE ) in transgenic poplars. In all these constructs, the expression of KNAT7 transgenes was driven by developing xylem (DX)-specific promoter, DX15. Compared to wild-type (WT) controls, many SCW biosynthesis genes downstream of KNAT7 were highly expressed in poplar PtKNAT7-OE and AtKNAT7-OE lines. Yet, no significant increase in lignin content of woody biomass of these transgenic lines was observed. PtKNAT7-AS lines, however, showed reduced expression of many SCW biosynthesis genes downstream of KNAT7 accompanied by a reduction in lignin content of wood compared to WT controls. Syringyl to Guaiacyl lignin (S/G) ratios were significantly increased in all three KNAT7 knockdown and overexpression transgenic lines than WT controls. These transgenic lines were essentially indistinguishable from WT controls in terms of their growth phenotype. Saccharification efficiency of woody biomass was significantly increased in all transgenic lines than WT controls. Overall, our results demonstrated that developing xylem-specific alteration of KNAT7 expression affects the expression of SCW biosynthesis genes, impacting at least the lignification process and improving saccharification efficiency, hence providing one of the powerful tools for improving bioethanol production from woody biomass of bioenergy crops and trees.
Switchgrass (Panicum virgatum L.) has immense potential as a bioenergy crop with the aim of producing biofuel as an end goal. Nitrogen (N)-related sustainability traits, such as nitrogen use efficiency (NUE) and nitrogen remobilization efficiency (NRE), are important factors affecting switchgrass quality and productivity. Hence, it is imperative to develop nitrogen use-efficient switchgrass accessions by exploring the genetic basis of NUE in switchgrass. For that, we used 331 diverse field-grown switchgrass accessions planted under low and moderate N fertility treatments. We performed a genome wide association study (GWAS) in a holistic manner where we not only considered NUE as a single trait but also used its related phenotypic traits, such as total dry biomass at low N and moderate N, and nitrogen use index, such as NRE. We have evaluated the phenotypic characterization of the NUE and the related traits, highlighted their relationship using correlation analysis, and identified the top ten nitrogen use-efficient switchgrass accessions. Our GWAS analysis identified 19 unique single nucleotide polymorphisms (SNPs) and 32 candidate genes. Two promising GWAS candidate genes, caffeoyl-CoA O-methyltransferase (CCoAOMT) and <alfin-like 6(AL6), were further supported by linkage disequilibrium (LD) analysis. Finally, we discussed the potential role of nitrogen in modulating the expression of these two genes. Our findings have opened avenues for the development of improved nitrogen use-efficient switchgrass lines.
Non-conventional yeasts are emerging as powerful alternatives to Saccharomyces cerevisiae for metabolic engineering, owing to their innate stress tolerance, broad substrate utilization, and distinctive metabolic capabilities. These attributes position them as promising chassis for producing biofuels, pharmaceuticals, and specialty chemicals. This review synthesizes recent advances in genetic toolkits for four such species—Pichia kudriavzevii (Issatchenkia orientalis), Starmerella bombicola, Debaryomyces hansenii, and Pachysolen tannophilus—highlighting progress across plasmid architectures (episomal and integrative), identification of autonomously replicating sequences and centromeric elements, and the development of safe-harbor genomic loci. We summarize promoter and terminator libraries enabling tunable expression, the expansion of auxotrophic and antifungal selection markers with recycling strategies, and the rapid adaptation of CRISPR-based systems (Cas9 and Cas12a) with optimized guide RNA expression, multiplex editing, and approaches that enhance homologous recombination (e.g., KU70/80 disruption). We also review landing-pad platforms for modular, repeated integrations and transposon-based tools (e.g., piggyBac) that facilitate multigene pathway assembly. Collectively, these innovations are accelerating design-build-test-learn cycles and enabling precise, scalable engineering of non-conventional yeasts. Remaining challenges—including limited species-specific episomal systems, variable transformation efficiencies, genome-stability concerns, and alternative codon usage—define clear priorities for future toolkit development. Together, these advances and open needs chart a path toward robust, sustainable biomanufacturing using diverse non-conventional yeast chassis.
Penetration of the power grid by renewable energy sources, distributed storage, and distributed generators is becoming increasingly common. Increased utilization of these distributed energy resources (DERs) has given rise to additional protection coordination concerns, particularly where they are utilized in an unbalanced manner or where loading among phases is unbalanced. Digital relays such as the SEL-751 (produced by Schweitzer Engineering Laboratories, Pullman, WA, USA) series have the capability of being set on a per-phase basis. This capability is underutilized in common practice. Additionally, in optimization algorithms for determining relay settings, the time-overcurrent characteristics (TOCs) of relays are generally not treated as variables and are assigned before running the optimization algorithm. In this paper, TOC options themselves are treated as discrete variables to be considered in the optimization algorithm. A mixed integer nonlinear programming problem (MINLP) is set up where the goal is to minimize relay operating times. A genetic algorithm (GA) approach is implemented in MATLAB where two cases are considered. In the first case, the TOC and Time dial setting (TDS) of each relay is set on a three-phase basis. In the second case, per-phase settings are considered. Relay TDSs and TOCs are both considered as simultaneous discrete control variables. Despite the stochastic nature of using per-phase settings for unbalanced systems is found to generally allow for shorter operating times. However, for relatively balanced systems, it is best to use three-phase settings if computation time is of importance.
Ice-binding proteins (IBPs) are a group of ecologically and biotechnologically relevant enzymes produced by psychrophilic organisms. Although putative IBPs containing the domain of unknown function (DUF) 3494 have been identified in many taxa of polar microbes, our knowledge of their genetic and structural diversity in natural microbial communities is limited. Here, we used samples from sea ice and sea water collected in the central Arctic Ocean as part of the MOSAiC expedition for metagenome sequencing and the subsequent analyses of metagenome-assembled genomes (MAGs). By linking structurally diverse IBPs to particular environments and potential functions, we reveal that IBP sequences are enriched in interior ice, have diverse genomic contexts and cluster taxonomically. Their diverse protein structures may be a consequence of domain shuffling, leading to variable combinations of protein domains in IBPs and probably reflecting the functional versatility required to thrive in the extreme and variable environment of the central Arctic Ocean.
The Ganoderma species in Polyporales are ecologically and economically relevant wood decayers used in traditional medicine, but their genomic traits are still poorly documented. In the present study, we carried out a phylogenomic and comparative genomic analyses to better understand the genetic blueprint of this fungal lineage. We investigated seven Ganoderma genomes, including three new genomes, G. australe, G. leucocontextum, and G. lingzhi. The size of the newly sequenced genomes ranged from 60.34 to 84.27 Mb and they encoded 15,007 to 20,460 genes. A total of 58 species, including 40 white-rot fungi, 11 brown-rot fungi, four ectomycorrhizal fungi, one endophyte fungus, and two pathogens in Basidiomycota, were used for phylogenomic analyses based on 143 single-copy genes. It confirmed that Ganoderma species belong to the core polyporoid clade. Comparing to the other selected species, the genomes of the Ganoderma species encoded a larger set of genes involved in terpene metabolism and coding for secreted proteins (CAZymes, lipases, proteases and SSPs). Of note, G. australe has the largest genome size with no obvious genome wide duplication, but showed transposable elements (TEs) expansion and the largest set of terpene gene clusters, suggesting a high ability to produce terpenoids for medicinal treatment. G. australe also encoded the largest set of proteins containing domains for cytochrome P450s, heterokaryon incompatibility and major facilitator families. Besides, the size of G. australe secretome is the largest, including CAZymes (AA9, GH18, A01A), proteases G01, and lipases GGGX, which may enhance the catabolism of cell wall carbohydrates, proteins, and fats during hosts colonization. The current genomic resource will be used to develop further biotechnology and medicinal applications, together with ecological studies of the Ganoderma species.