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At least 181 records · Page 10

Identification of pleiotropic loci mediating structural and non-structural carbohydrate accumulation within the sorghum bioenergy association panel using high-throughput markers

Molecular characterization of diverse germplasm can contribute to breeding programs by increasing genetic gain for sorghum [ Sorghum bicolor (L.) Moench] improvement. Identifying novel marker-trait associations and candidate genes enriches the existing genomic resources and can improve bioenergy-related traits using genomic-assisted breeding. In the current scenario, identifying the genetic loci underlying biomass and carbon partitioning is vital for ongoing efforts to maximize each carbon sink’s yield for bioenergy production. Here, we have processed a high-density genomic marker (22 466 550) data based on whole-genome sequencing (WGS) using a set of 365 accessions from the bioenergy association panel (BAP), which includes ~19.7 million (19 744 726) single nucleotide polymorphism (SNPs) and 2.7 million (~2 721 824) insertion deletions (indels). A set of high-quality filtered SNP (~5.48 million) derived markers facilitated the assessment of population structure, genetic diversity, and genome-wide association studies (GWAS) for various traits related to biomass and its composition using the BAP. The phenotypic traits for GWAS included seed color (SC), plant height (PH), days to harvest (DTH), fresh weight (FW), dry weight (DW), brix content % (BRX), neutral detergent fiber (NDF), acid detergent fiber (ADF), non-fibrous carbohydrate (NFC), and lignin content. Several novel loci and candidate genes were identified for bioenergy-related traits, and some well-characterized genes for plant height ( Dw1 and Dw2 ) and the YELLOW SEED1 locus ( Y1 ) were validated. We further performed a multi-variate adaptive shrinkage analysis to identify pleiotropic QTL, which resulted in several shared marker-trait associations among bioenergy and compositional traits. Significant marker-trait associations with pleiotropic effects can be used to develop molecular markers for trait improvement using a marker-assisted breeding approach. Significant nucleotide diversity and heterozygosity were observed between photoperiod-sensitive and insensitive individuals of the panel. This diverse bioenergy panel with genomic resources will provide an excellent opportunity for further genetic studies, including selecting parental lines for superior hybrid development to improve biomass-related traits in sorghum.

bioenergy association panel↗

The effect of protein mutations on drug binding suggests ensuing personalised drug selection

The advent of personalised medicine promises a deeper understanding of mechanisms and therefore therapies. However, the connection between genomic sequences and clinical treatments is often unclear. We studied 50 breast cancer patients belonging to a population-cohort in the state of Qatar. From Sanger sequencing, we identified several new deleterious mutations in the estrogen receptor 1 gene (ESR1). The effect of these mutations on drug treatment in the protein target encoded by ESR1, namely the estrogen receptor, was achieved via rapid and accurate protein–ligand binding affinity interaction studies which were performed for the selected drugs and the natural ligand estrogen. Four nonsynonymous mutations in the ligand-binding domain were subjected to molecular dynamics simulation using absolute and relative binding free energy methods, leading to the ranking of the efficacy of six selected drugs for patients with the mutations. Our study shows that a personalised clinical decision system can be created by integrating an individual patient’s genomic data at the molecular level within a computational pipeline which ranks the efficacy of binding of particular drugs to variant proteins.

59 BASIC BIOLOGICAL SCIENCES↗

Optimizing resource allocation in Miscanthus breeding via sparse testing designs for genomic prediction

Phenotyping high-biomass perennial crops is laborious and the rate of genetic gain in conventional perennial crop breeding programs is typically low. So, it is especially important to identify methods that produce efficiency gains in the breeding process. Miscanthus is a C4 perennial grass with favorable characteristics for producing biomass as a feedstock for biofuels and diverse bio-based products. Increasing biomass yield will increase profitability and environmental benefits, so it is a key target for Miscanthus breeding. In addition, the identification of well-adapted genotypes across a wide range of environmental conditions requires the establishment of multi-environment trials (METs). Sparse testing is a genomic prediction-based strategy that reduces the phenotyping costs in METs by selecting a subset of genotypes to evaluate in a subset of environments and then predicts the performance of the unobserved genotype-environment combinations. A Miscanthus sacchariflorus (MSA) population comprising 336 genotypes observed across three environments was analyzed implementing sparse testing designs. Three prediction models considering main effects (environments, genotypes, genomic) and interaction effects (genotype-by-environment; G×E interaction) were implemented for forecasting dry biomass yield (YDY), total culm (TCM), average internode length (AIL), and culm node number (CNN). Multiple calibration sets based on different compositions and sizes were considered to evaluate performance in terms of the predictive ability (PA) and the mean square error (MSE) for a fixed testing set size. The training set size ranged from 52 to 112 to predict a fixed set of 224 unobserved genotypes across all three environments. The results showed that the model accounting for G×E interaction consistently presented the highest PA and the lowest MSE: for CNN (PA: ~0.77, MSE: ~0.5) and YDY (PA: ~0.70, MSE: ~1.3) while for TCM and AIL these ranged from ~0.28 to 0.41 and ~1.3 to 4.3, respectively. Overall, varying training sets and allocation strategies did not affect PA and MSE, with 52 non-overlapping and 0 overlapping genotypes per environment as the optimal cost-effective allocation framework. This suggests that implementing sparse testing designs could significantly reduce phenotyping costs by fivefold, without compromising PA in breeding programs for perennial crops such as Miscanthus.

Miscanthus sacchariflorus (MSA)↗

Altering translation allows E. coli to overcome chemically stabilized G-quadruplexes

Genomic DNA from each sample was prepared using the Wizard Genomic DNA Purification Kit (Promega) and after, DNA was quantified using the QuantiFluor ONE dsDNA System (Promega). Genomic DNA underwent shearing to ~200 bp fragments via sonication and the gDNA fragments were prepared for sequencing using the NEBNext Ultra II DNA Library Prep Kit for Illumina (NEB). Bead-based size selection was used to select ~200 bp fragments and the fragments then underwent a splinkerette PCR using a Tn5-enriching forward primer and custom reverse primers for multiplexing. A final bead-based size selection was used to select for the correct length DNA. DNA was sequenced at the University of Michigan Advanced Genomics Core using Illumina sequencing with a custom read primer reading the last 10 nt of the transposon. PhiX174 DNA spike was added to the run to ensure sufficient sequence diversity on the flow cell. Then, a custom index read primer and standard Illumina primer were used to sequence the index reads and PhiX174, respectively.

Keck, James L.↗

Learning epistatic polygenic phenotypes with Boolean interactions

Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1 , a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments.

59 BASIC BIOLOGICAL SCIENCES↗

Stress-Driven Selection of Novel Phenotypes

A process has been developed that can confer novel properties, such as metal resistance, to a host bacterium. This same process can also be used to produce RNAs and peptides that have novel properties, such as the ability to bind particular compounds. It is inherent in the method that the peptide or RNA will behave as expected in the target organism. Plasmid-born mini-gene libraries coding for either a population of combinatorial peptides or stable, artificial RNAs carrying random inserts are produced. These libraries, which have no bias towards any biological function, are used to transform the organism of interest and to serve as an initial source of genetic variation for stress-driven evolution. The transformed bacteria are propagated under selective pressure in order to obtain variants with the desired properties. The process is highly distinct from in vitro methods because the variants are selected in the context of the cell while it is experiencing stress. Hence, the selected peptide or RNA will, by definition, work as expected in the target cell as the cell adapts to its presence during the selection process. Once the novel gene, which produces the sought phenotype, is obtained, it can be transferred to the main genome to increase the genetic stability in the organism. Alternatively, the cell line can be used to produce novel RNAs or peptides with selectable properties in large quantity for separate purposes. The system allows for easy, large-scale purification of the RNAs or peptide products. The process has been reduced to practice by imposing sub-inhibitory concentrations of NiCl2 on cells of the bacterium Escherichia coli that were transformed separately with the peptide library and RNA library. The evolved resistant clones were isolated, and sequences of the selected mini-gene variants were established. Clones resistant to NiCl2 were found to carry identical plasmid variants with a functional mini-gene that specifically conferred significant nickel tolerance on the host cells. Sequencing of the selected mini-gene revealed a propensity of the encoded peptide to bind transient metal ions. Expression of the mini-gene markedly improved growth parameters of the evolved clones at sub-inhibitory concentrations of NiCl2 while being slightly detrimental in the absence of stress. Similar results have been obtained with the RNA libraries. Overall, the results demonstrate a very natural outcome of the selection experiments in which the mini-genes were expected to be either successfully integrated into bacterial genetic networks, or rejected depending upon their effect on host fitness. This described approach can be useful as a laboratory model to study the dynamics of bacterial adaptive evolution on the molecular level. It can also provide a strategy for screening expressed DNA libraries in search of novel genes with desirable properties.

Fox, George E.↗

Cas9-Based Metabolic Engineering of Issatchenkia orientalis for Enhanced Utilization of Cellulosic Hydrolysates

Issatchenkia orientalis, exhibiting high tolerance against harsh environmental conditions, is a promising metabolic engineering host for producing fuels and chemicals from cellulosic hydrolysates containing fermentation inhibitors under acidic conditions. Although genetic tools for I. orientalis exist, they require auxotrophic mutants so that the selection of a host strain is limited. We developed a drug resistance gene (cloNAT)-based genome-editing method for engineering any I. orientalis strains and engineered I. orientalis strains isolated from various sources for xylose fermentation. Specifically, xylose reductase, xylitol dehydrogenase, and xylulokinase from Scheffersomyces stipitis were integrated into an intended chromosomal locus in four I. orientalis strains (SD108, IO21, IO45, and IO46) through Cas9-based genome editing. Furthermore, the resulting strains (SD108X, IO21X, IO45X, and IO46X) efficiently produced ethanol from cellulosic and hemicellulosic hydrolysates even though the pH adjustment and nitrogen source were not provided. As they presented different fermenting capacities, selection of a host I. orientalis strain was crucial for producing fuels and chemicals using cellulosic hydrolysates.

09 BIOMASS FUELS↗

A large sequenced mutant library – valuable reverse genetic resource that covers 98% of sorghum genes

SUMMARY Mutant populations are crucial for functional genomics and discovering novel traits for crop breeding. Sorghum , a drought and heat‐tolerant C4 species, requires a vast, large‐scale, annotated, and sequenced mutant resource to enhance crop improvement through functional genomics research. Here, we report a sorghum large‐scale sequenced mutant population with 9.5 million ethyl methane sulfonate (EMS)‐induced mutations that covered 98% of sorghum's annotated genes using inbred line BTx623. Remarkably, a total of 610 320 mutations within the promoter and enhancer regions of 18 000 and 11 790 genes, respectively, can be leveraged for novel research of cis ‐regulatory elements. A comparison of the distribution of mutations in the large‐scale mutant library and sorghum association panel (SAP) provides insights into the influence of selection. EMS‐induced mutations appeared to be random across different regions of the genome without significant enrichment in different sections of a gene, including the 5′ UTR, gene body, and 3′‐UTR. In contrast, there were low variation density in the coding and UTR regions in the SAP. Based on the K a / K s value, the mutant library (~1) experienced little selection, unlike the SAP (0.40), which has been strongly selected through breeding. All mutation data are publicly searchable through SorbMutDB ( https://www.depts.ttu.edu/igcast/sorbmutdb.php ) and SorghumBase ( https://sorghumbase.org/ ). This current large‐scale sequence‐indexed sorghum mutant population is a crucial resource that enriched the sorghum gene pool with novel diversity and a highly valuable tool for the Poaceae family, that will advance plant biology research and crop breeding.

59 BASIC BIOLOGICAL SCIENCES↗

Genomic and Phenotypic Characterization of Yeast Biosensor for Deep-space Radiation

The BioSentinel mission was selected to launch as a secondary payload onboard NASA Exploration Mission 1 (EM-1) in 2018. In BioSentinel, the budding yeast Saccharomyces cerevisiae will be used as a biosensor to measure the long-term impact of deep-space radiation to living organisms. In the 4U-payload, desiccated yeast cells from different strains will be stored inside microfluidic cards equipped with 3-color LED optical detection system to monitor cell growth and metabolic activity. At different times throughout the 12-month mission, these cards will be filled with liquid yeast growth media to rehydrate and grow the desiccated cells. The growth and metabolic rates of wild-type and radiation-sensitive strains in deep-space radiation environment will be compared to the rates measured in the ground- and microgravity-control units. These rates will also be correlated with measurements obtained from onboard physical dosimeters. In our preliminary long-term desiccation study, we found that air-drying yeast cells in 10% trehalose is the best method of cell preservation in order to survive the entire 18-month mission duration (6-month pre-launch plus 12-month full-mission periods). However, our study also revealed that desiccated yeast cells have decreasing viability over time when stored in payload-like environment. This suggests that the yeast biosensor will have different population of cells at different time points during the long-term mission. In this study, we are characterizing genomic and phenotypic changes in our yeast biosensor due to long-term storage and desiccation. For each yeast strain that will be part of the biosensor, several clones were reisolated after long-term storage by desiccation. These clones were compared to their respective original isolate in terms of genomic composition, desiccation tolerance and radiation sensitivity. Interestingly, clones from a radiation-sensitive mutant have better desiccation tolerance compared to their original isolate without losing radiation sensitivity. We employed Next-Generation Sequencing technology to better understand this phenotypic variation. Current effort is focusing on the analysis of high-throughput sequencing data to look for genomic changes in these reisolated clones compared to their original isolate.

yeast↗

Amino acid substrate specificities and tissue expression profiles of the nine CYP79A encoding genes in Sorghum bicolor

Cytochrome P450s of the CYP79 family catalyze two N-hydroxylation reactions, converting a selected number of amino acids into the corresponding oximes. The sorghum genome (Sorghum bicolor) harbours nine CYP79A encoding genes, and here sequence comparisons of the CYP79As along with their substrate recognition sites (SRSs) are provided. The substrate specificity of previously uncharacterized CYP79As was investigated by transient expression in Nicotiana benthamiana and subsequent transformation of the oximes formed into the corresponding stable oxime glucosides catalyzed by endogenous UDPG-glucosyltransferases (UGTs). CYP79A61 uses phenylalanine as a substrate, whereas CYP79A91, CYP79A93, and CYP79A95 use valine and isoleucine as substrates, with CYP79A93 showing the ability also to use phenylalanine. CYP79A94 uses isoleucine as a substrate. Analysis of 249 sorghum transcriptomes from two different sorghum cultivars showed the expression levels and tissue-specific expression of the CYP79As. CYP79A1 is the committed gene in dhurrin formation and was the highest expressed gene in most tissues/organs. CYP79A61 was primarily expressed in fully developed leaf blades and leaf sheaths. CYP79A91 and CYP79A92 were expressed mainly in roots >200 cm below ground, while CYP79A93 and CYP79A94 were most highly expressed in the leaf collar and leaf sheath, respectively. Here, the possible signalling effects of the oximes and their metabolites produced in different sorghum tissues are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

Deep Green: Structural and Functional Genomic Characterization of Conserved Unannotated Green Lineage Proteins

Our overall objective is to improve and increase functional and structural predictions for a growing number of plant proteins of unknown structure and function (the Deep Green proteins), and to make our predictive data useful and accessible to the larger research community. The project is divided into five major objectives which include 1) Assembly and curation of Deep Green candidate protein sets; 2) in silico structural and functional predictions and network analyses; 3) assembly and validation of reverse genetic resources in Chlamydomonas reinhardtii (Chlamydomonas); 4) high throughput functional genomics characterization and prioritization in Chlamydomonas; and 5) structural validation of selected candidates and functional validation in two important reference plant species, Arabidopsis thaliana (Arabidopsis) and Setaria viridis (Setaria).

59 BASIC BIOLOGICAL SCIENCES↗

From Reads to Function Workshop - Milano 2026

The Bicocca Sampling Days (BSDs) model offers a reproducible “citizen science” framework integrating research, education, and public engagement through large-scale microbiome sampling, followed by a workshop of data analysis on select samples. We identified 9 bacterial and archaeal metagenome-assembled genomes from six soil samples across three separate sampling days in two approaches with indidivual sample and replicate co-assembly spanning three unique classes, providing genomic insights into microbial nutrient cycling in these systems.

59 BASIC BIOLOGICAL SCIENCES↗

Structure and flexibility of the yeast NuA4 histone acetyltransferase complex

The NuA4 protein complex acetylates histones H4 and H2A to activate both transcription and DNA repair. We report the 3.1-Å resolution cryo-electron microscopy structure of the central hub of NuA4, which flexibly tethers the histone acetyltransferase (HAT) and Trimer Independent of NuA4 involved in Transcription Interactions with Nucleosomes (TINTIN) modules. The hub contains the large Tra1 subunit and a core that includes Swc4, Arp4, Act1, Eaf1, and the C-terminal region of Epl1. Eaf1 stands out as the primary scaffolding factor that interacts with the Tra1, Swc4, and Epl1 subunits and contributes the conserved HSA helix to the Arp module. Using nucleosome-binding assays, we find that the HAT module, which is anchored to the core through Epl1, recognizes H3K4me3 nucleosomes with hyperacetylated H3 tails, while the TINTIN module, anchored to the core via Eaf1, recognizes nucleosomes that have hyperacetylated H2A and H4 tails. Together with the known interaction of Tra1 with site-specific transcription factors, our data suggest a model in which Tra1 recruits NuA4 to specific genomic sites then allowing the flexible HAT and TINTIN modules to select nearby nucleosomes for acetylation.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic dissection of natural variation in oilseed traits of camelina by whole‐genome resequencing and QTL mapping

Abstract Camelina [ Camelina sativa (L.) Crantz] is an oilseed crop in the Brassicaceae family that is currently being developed as a source of bioenergy and healthy fatty acids. To facilitate modern breeding efforts through marker‐assisted selection and biotechnology, we evaluated genetic variation among a worldwide collection of 222 camelina accessions. We performed whole‐genome resequencing to obtain single nucleotide polymorphism (SNP) markers and to analyze genomic diversity. We also conducted phenotypic field evaluations in two consecutive seasons for variations in key agronomic traits related to oilseed production such as seed size, oil content (OC), fatty acid composition, and flowering time. We determined the population structure of the camelina accessions using 161,301 SNPs. Further, we identified quantitative trait loci (QTL) and candidate genes controlling the above field‐evaluated traits by genome‐wide association studies (GWAS) complemented with linkage mapping using a recombinant inbred line (RIL) population. Characterization of the natural variation at the genome and phenotypic levels provides valuable resources to camelina genetic studies and crop improvement. The QTL and candidate genes should assist in breeding of advanced camelina varieties that can be integrated into the cropping systems for the production of high yield of oils of desired fatty acid composition.

59 BASIC BIOLOGICAL SCIENCES↗

An essential and highly selective protein import pathway encoded by nucleus-forming phage

Targeting proteins to specific subcellular destinations is essential in prokaryotes, eukaryotes, and the viruses that infect them. Chimalliviridae phages encapsulate their genomes in a nucleus-like replication compartment composed of the protein chimallin (ChmA) that excludes ribosomes and decouples transcription from translation. These phages selectively partition proteins between the phage nucleus and the bacterial cytoplasm. Currently, the genes and signals that govern selective protein import into the phage nucleus are unknown. Here, we identify two components of this protein import pathway: a species-specific surface-exposed region of a phage intranuclear protein required for nuclear entry and a conserved protein, PicA (Protein importer of chimalliviruses A), that facilitates cargo protein trafficking across the phage nuclear shell. We also identify a defective cargo protein that is targeted to PicA on the nuclear periphery but fails to enter the nucleus, providing insight into the mechanism of nuclear protein trafficking. Using CRISPRi-ART protein expression knockdown of PicA, we show that PicA is essential early in the chimallivirus replication cycle. Together, our results allow us to propose a multistep model for the Protein Import Chimallivirus pathway, where proteins are targeted to PicA by amino acids on their surface and then licensed by PicA for nuclear entry. The divergence in the selectivity of this pathway between closely related chimalliviruses implicates its role as a key player in the evolutionary arms race between competing phages and their hosts.

59 BASIC BIOLOGICAL SCIENCES↗

Switchgrass sward establishment selection is consistent across multiple environments and fertilization levels

Strong selection can occur during switchgrass sward establishment. Differences in establishment selection due to environment or management could provide information on genotype-by-environment variation and could influence strategies for breeding perennial grasses. Leaf samples were collected before sward establishment and from 3-year-old swards for two breeding groups (lowland and hybrid) at three locations. Within two locations, samples were collected from paired fertilized (112 kg N ha –1 ) and unfertilized plots. Allele frequencies from pooled DNA samples were studied through multivariate analysis of variance, genomewide trait predictions (heading date and winter survivorship), and genomically estimated breeding values (GEBVs) for individual sward survival within an independent data set. This study found only minor variations in selection due to location or management. Predicted heading dates of the hybrid population had significant changes due to fertilization and location. There were strong correlations among sward establishment survival GEBVs between growing environments (hybrid r = 0.77; gulf r = 0.97). Interestingly, this study found a small number of genotypes that were over-represented in established swards across all growing environments. This study reinforces a prior report of selection during sward establishment and indicates that only a small degree of establishment selection is location-specific within these diverse growing conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Genome‐wide association study of multiple yield traits in a diversity panel of polyploid sugarcane ( Saccharum spp.)

Abstract Sugarcane ( Saccharum spp.) is an important economic crop, contributing up to 80% of sugar and approximately 60% of biofuel globally. To meet the increased demand for sugar and biofuel supplies, it is critical to breed sugarcane cultivars with robust performance in yield traits. Therefore, dissection of causal DNA sequence variants is of great importance, as it provides genetic resources and fundamental information for crop improvement. In this study, we analyzed nine yield traits in a sugarcane diversity panel consisting of 308 accessions primarily selected from the World Collection of Sugarcane and Related Grasses. By genotyping the diversity panel via target enrichment sequencing, we identified a large number of sequence variants. Genome‐wide association studies between the markers and traits were conducted, taking dosages and gene actions into consideration. In total, 217 nonredundant markers and 225 candidate genes were identified to be significantly associated with the yield traits, which can serve as a comprehensive genetic resource database for future gene identification, characterization, and selection for sugarcane improvement. We further investigated runs of homozygosity (ROH) in the sugarcane diversity panel. We characterized 282 ROHs and found that the occurrence of ROHs in the genome were nonrandom and probably under selection. The ROHs were associated with total weight and dry weight, and high ROHs resulted in a decrease in the two traits. This study suggests that genomic inbreeding has led to negative impacts on sugarcane yield.

Yang, Xiping↗

Genome-resolved analysis of Serratia marcescens strain SMTT infers niche specialization as a hydrocarbon-degrader

Abstract Bacteria that are chronically exposed to high levels of pollutants demonstrate genomic and corresponding metabolic diversity that complement their strategies for adaptation to hydrocarbon-rich environments. Whole genome sequencing was carried out to infer functional traits of Serratia marcescens strain SMTT recovered from soil contaminated with crude oil. The genome size (Mb) was 5,013,981 with a total gene count of 4,842. Comparative analyses with carefully selected S. marcescens strains, 2 of which are associated with contaminated soil, show conservation of central metabolic pathways in addition to intra-specific genetic diversity and metabolic flexibility. Genome comparisons also indicated an enrichment of genes associated with multidrug resistance and efflux pumps for SMTT. The SMTT genome contained genes that enable the catabolism of aromatic compounds via the protocatechuate para-degradation pathway, in addition to meta-cleavage of catechol (meta-cleavage pathway II); gene enrichment for aromatic compound degradation was markedly higher for SMTT compared to the other S. marcescens strains analysed. Our data presents a valuable genetic inventory for future studies on strains of S. marcescens and provides insights into those genomic features of SMTT with industrial potential.

Genetics & Heredity↗