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Modeling and computational characterization of a Xanthomonas sp. Hypothetical protein identifies a remote ortholog of Burkholderia lethal factor 1

Muhamad Ismail NAS, Yap SH, Mohamad Yussoff MA, Nor Muhammad NA, Firdaus-Raih M, Quay DHX

J Biomol Struct Dyn, 2023;41(13):6027-6039.
PMID: 35862639 DOI: 10.1080/07391102.2022.2100827

Burkholderia Lethal Factor 1 (BLF1) is a deamidase first characterized in Burkholderia pseudomallei. This enzyme inhibits cellular protein synthesis by deamidating a glutamine residue to a glutamic acid in its target protein, the eukaryotic translation initiation factor 4 A (eIF4A). In this work, we present the characterization of a hypothetical protein from Xanthomonas sp. Leaf131 as the first report of a BLF1 family ortholog outside of the Burkholderia genus. Although standard sequence similarity searches such as BLAST were not able to detect the homology between the Xanthomonas sp. Leaf131 hypothetical protein sequence and BLF1, our computed structure model for the Xanthomonas sp. hypothetical protein revealed structural similarities with an RMSD of 2.7 Å/164 Cα atoms and a TM-score of 0.72 when superposed. Structural comparisons of the Xanthomonas model structure against BLF1 and Escherichia coli cytotoxic necrotizing factor 1 (CNF1) revealed that the conserved signature LXGC motif and putative catalytic residues are structurally aligned thus signifying a level of functional or mechanistic similarity. Protein-protein docking analysis and molecular dynamics simulations also demonstrated that eIF4A could still be a possible target substrate for deamidation by XLF1 as it is for BLF1. We therefore propose that this Xanthomonas hypothetical protein be renamed as Xanthomonas Lethal Factor 1 (XLF1). Our work also provides further evidence of the utility of programs such as AlphaFold in bridging the computational function annotation transfer gap despite very low sequence identities of under 20%.Communicated by Ramaswamy H. Sarma.
Fulltext NASSAM: a server to search for and annotate tertiary interactions and motifs in three-dimensional structures of complex RNA molecules

Hamdani HY, Appasamy SD, Willett P, Artymiuk PJ, Firdaus-Raih M

Nucleic Acids Res, 2012 Jul;40(Web Server issue):W35-41.
PMID: 22661578 DOI: 10.1093/nar/gks513

Similarities in the 3D patterns of RNA base interactions or arrangements can provide insights into their functions and roles in stabilization of the RNA 3D structure. Nucleic Acids Search for Substructures and Motifs (NASSAM) is a graph theoretical program that can search for 3D patterns of base arrangements by representing the bases as pseudo-atoms. The geometric relationship of the pseudo-atoms to each other as a pattern can be represented as a labeled graph where the pseudo-atoms are the graph's nodes while the edges are the inter-pseudo-atomic distances. The input files for NASSAM are PDB formatted 3D coordinates. This web server can be used to identify matches of base arrangement patterns in a query structure to annotated patterns that have been reported in the literature or that have possible functional and structural stabilization implications. The NASSAM program is freely accessible without any login requirement at http://mfrlab.org/grafss/nassam/.
Fulltext Nematode Peptides with Host-Directed Anti-inflammatory Activity Rescue Caenorhabditis elegans from a Burkholderia pseudomallei Infection

Lim MP, Firdaus-Raih M, Nathan S

Front Microbiol, 2016;7:1436.
PMID: 27672387 DOI: 10.3389/fmicb.2016.01436

Burkholderia pseudomallei, the causative agent of melioidosis, is among a growing number of bacterial pathogens that are increasingly antibiotic resistant. Antimicrobial peptides (AMPs) have been investigated as an alternative approach to treat microbial infections, as generally, there is a lower likelihood that a pathogen will develop resistance to AMPs. In this study, 36 candidate Caenorhabditis elegans genes that encode secreted peptides of <150 amino acids and previously shown to be overexpressed during infection by B. pseudomallei were identified from the expression profile of infected nematodes. RNA interference (RNAi)-based knockdown of 12/34 peptide-encoding genes resulted in enhanced nematode susceptibility to B. pseudomallei without affecting worm fitness. A microdilution test demonstrated that two peptides, NLP-31 and Y43C5A.3, exhibited anti-B. pseudomallei activity in a dose dependent manner on different pathogens. Time kill analysis proposed that these peptides were bacteriostatic against B. pseudomallei at concentrations up to 8× MIC90. The SYTOX green assay demonstrated that NLP-31 and Y43C5A.3 did not disrupt the B. pseudomallei membrane. Instead, gel retardation assays revealed that both peptides were able to bind to DNA and interfere with bacterial viability. In parallel, microscopic examination showed induction of cellular filamentation, a hallmark of DNA synthesis inhibition, of NLP-31 and Y43C5A.3 treated cells. In addition, the peptides also regulated the expression of inflammatory cytokines in B. pseudomallei infected macrophage cells. Collectively, these findings demonstrate the potential of NLP-31 and Y43C5A.3 as anti-B. pseudomallei peptides based on their function as immune modulators.
Fulltext Perigone Lobe Transcriptome Analysis Provides Insights into Rafflesia cantleyi Flower Development

Lee XW, Mat-Isa MN, Mohd-Elias NA, Aizat-Juhari MA, Goh HH, Dear PH, et al.

PLoS One, 2016;11(12):e0167958.
PMID: 27977777 DOI: 10.1371/journal.pone.0167958

Rafflesia is a biologically enigmatic species that is very rare in occurrence and possesses an extraordinary morphology. This parasitic plant produces a gigantic flower up to one metre in diameter with no leaves, stem or roots. However, little is known about the floral biology of this species especially at the molecular level. In an effort to address this issue, we have generated and characterised the transcriptome of the Rafflesia cantleyi flower, and performed a comparison with the transcriptome of its floral bud to predict genes that are expressed and regulated during flower development. Approximately 40 million sequencing reads were generated and assembled de novo into 18,053 transcripts with an average length of 641 bp. Of these, more than 79% of the transcripts had significant matches to annotated sequences in the public protein database. A total of 11,756 and 7,891 transcripts were assigned to Gene Ontology categories and clusters of orthologous groups respectively. In addition, 6,019 transcripts could be mapped to 129 pathways in Kyoto Encyclopaedia of Genes and Genomes Pathway database. Digital abundance analysis identified 52 transcripts with very high expression in the flower transcriptome of R. cantleyi. Subsequently, analysis of differential expression between developing flower and the floral bud revealed a set of 105 transcripts with potential role in flower development. Our work presents a deep transcriptome resource analysis for the developing flower of R. cantleyi. Genes potentially involved in the growth and development of the R. cantleyi flower were identified and provide insights into biological processes that occur during flower development.
ProLysED: an integrated database and meta-server of bacterial protease systems

Firdaus Raih M, Ahmad HA, Sharum MY, Azizi N, Mohamed R

Appl. Bioinformatics, 2005;4(2):147-50.
PMID: 16128617

Bacterial proteases are an important group of enzymes that have very diverse biochemical and cellular functions. Proteases from prokaryotic sources also have a wide range of uses, either in medicine as pathogenic factors or in industry and therapeutics. ProLysED (Prokaryotic Lysis Enzymes Database), our meta-server integrated database of bacterial proteases, is a useful, albeit very niche, resource. The features include protease classification browsing and searching, organism-specific protease browsing, molecular information and visualisation of protease structures from the Protein Data Bank (PDB) as well as predicted protease structures.
Fulltext Proteins of unknown function in the Protein Data Bank (PDB): an inventory of true uncharacterized proteins and computational tools for their analysis

Nadzirin N, Firdaus-Raih M

Int J Mol Sci, 2012;13(10):12761-72.
PMID: 23202924 DOI: 10.3390/ijms131012761

Proteins of uncharacterized functions form a large part of many of the currently available biological databases and this situation exists even in the Protein Data Bank (PDB). Our analysis of recent PDB data revealed that only 42.53% of PDB entries (1084 coordinate files) that were categorized under "unknown function" are true examples of proteins of unknown function at this point in time. The remainder 1465 entries also annotated as such appear to be able to have their annotations re-assessed, based on the availability of direct functional characterization experiments for the protein itself, or for homologous sequences or structures thus enabling computational function inference.
Reconstructing gene regulatory networks from knock-out data using Gaussian Noise Model and Pearson Correlation Coefficient

Mohamed Salleh FH, Arif SM, Zainudin S, Firdaus-Raih M

Comput Biol Chem, 2015 Dec;59 Pt B:3-14.
PMID: 26278974 DOI: 10.1016/j.compbiolchem.2015.04.012

A gene regulatory network (GRN) is a large and complex network consisting of interacting elements that, over time, affect each other's state. The dynamics of complex gene regulatory processes are difficult to understand using intuitive approaches alone. To overcome this problem, we propose an algorithm for inferring the regulatory interactions from knock-out data using a Gaussian model combines with Pearson Correlation Coefficient (PCC). There are several problems relating to GRN construction that have been outlined in this paper. We demonstrated the ability of our proposed method to (1) predict the presence of regulatory interactions between genes, (2) their directionality and (3) their states (activation or suppression). The algorithm was applied to network sizes of 10 and 50 genes from DREAM3 datasets and network sizes of 10 from DREAM4 datasets. The predicted networks were evaluated based on AUROC and AUPR. We discovered that high false positive values were generated by our GRN prediction methods because the indirect regulations have been wrongly predicted as true relationships. We achieved satisfactory results as the majority of sub-networks achieved AUROC values above 0.5.
Regulation of Glycine Cleavage and Detoxification by a Highly Conserved Glycine Riboswitch in Burkholderia spp

Munyati-Othman N, Appasamy SD, Damiri N, Emrizal R, Alipiah NM, Ramlan EI, et al.

Curr Microbiol, 2021 Aug;78(8):2943-2955.
PMID: 34076709 DOI: 10.1007/s00284-021-02550-5

The glycine riboswitch is a known regulatory element that is unique in having two aptamers that are joined by a linker region. In this study, we investigated a glycine riboswitch located in the 5' untranslated region of a glycine cleavage system homolog (gcvTHP) in Burkholderia spp. Structure prediction using the sequence generated a model with a glycine binding pocket composed of base-triple interactions (G62-A64-A86 and G65-U84-C85) that are supported by A/G minor interactions (A17-C60-G88 and G16-C61-G87, respectively) and two ribose-zipper motifs (C11-G12 interacting with A248-A247 and C153-U154 interacting with A79-A78) which had not been previously reported. The capacity of the riboswitch to bind to glycine was experimentally validated by native gel assays and the crucial role of interactions that make up the glycine binding pocket were proven by mutations of A17U and G16C which resulted in conformational differences that may lead to dysfunction. Using glycine supplemented minimal media, we were able to prove that the expression of the gcvTHP genes found downstream of the riboswitch responded to the glycine concentrations introduced thus confirming the role of this highly conserved Burkholderia riboswitch and its associated genes as a putative glycine detoxification system in Burkholderia spp.
Fulltext SPRITE and ASSAM: web servers for side chain 3D-motif searching in protein structures

Nadzirin N, Gardiner EJ, Willett P, Artymiuk PJ, Firdaus-Raih M

Nucleic Acids Res, 2012 Jul;40(Web Server issue):W380-6.
PMID: 22573174 DOI: 10.1093/nar/gks401

Similarities in the 3D patterns of amino acid side chains can provide insights into their function despite the absence of any detectable sequence or fold similarities. Search for protein sites (SPRITE) and amino acid pattern search for substructures and motifs (ASSAM) are graph theoretical programs that can search for 3D amino side chain matches in protein structures, by representing the amino acid side chains as pseudo-atoms. The geometric relationship of the pseudo-atoms to each other as a pattern can be represented as a labeled graph where the pseudo-atoms are the graph's nodes while the edges are the inter-pseudo-atomic distances. Both programs require the input file to be in the PDB format. The objective of using SPRITE is to identify matches of side chains in a query structure to patterns with characterized function. In contrast, a 3D pattern of interest can be searched for existing occurrences in available PDB structures using ASSAM. Both programs are freely accessible without any login requirement. SPRITE is available at http://mfrlab.org/grafss/sprite/ while ASSAM can be accessed at http://mfrlab.org/grafss/assam/.
Self-assembly programming of DNA polyominoes

Ong HS, Syafiq-Rahim M, Kasim NH, Firdaus-Raih M, Ramlan EI

J Biotechnol, 2016 Oct 20;236:141-51.
PMID: 27569553 DOI: 10.1016/j.jbiotec.2016.08.017

Fabrication of functional DNA nanostructures operating at a cellular level has been accomplished through molecular programming techniques such as DNA origami and single-stranded tiles (SST). During implementation, restrictive and constraint dependent designs are enforced to ensure conformity is attainable. We propose a concept of DNA polyominoes that promotes flexibility in molecular programming. The fabrication of complex structures is achieved through self-assembly of distinct heterogeneous shapes (i.e., self-organised optimisation among competing DNA basic shapes) with total flexibility during the design and assembly phases. In this study, the plausibility of the approach is validated using the formation of multiple 3×4 DNA network fabricated from five basic DNA shapes with distinct configurations (monomino, tromino and tetrominoes). Computational tools to aid the design of compatible DNA shapes and the structure assembly assessment are presented. The formations of the desired structures were validated using Atomic Force Microscopy (AFM) imagery. Five 3×4 DNA networks were successfully constructed using combinatorics of these five distinct DNA heterogeneous shapes. Our findings revealed that the construction of DNA supra-structures could be achieved using a more natural-like orchestration as compared to the rigid and restrictive conventional approaches adopted previously.
Fulltext Seqping: gene prediction pipeline for plant genomes using self-training gene models and transcriptomic data

Chan KL, Rosli R, Tatarinova TV, Hogan M, Firdaus-Raih M, Low EL

BMC Bioinformatics, 2017 Jan 27;18(Suppl 1):1426.
PMID: 28466793 DOI: 10.1186/s12859-016-1426-6

BACKGROUND: Gene prediction is one of the most important steps in the genome annotation process. A large number of software tools and pipelines developed by various computing techniques are available for gene prediction. However, these systems have yet to accurately predict all or even most of the protein-coding regions. Furthermore, none of the currently available gene-finders has a universal Hidden Markov Model (HMM) that can perform gene prediction for all organisms equally well in an automatic fashion.
RESULTS: We present an automated gene prediction pipeline, Seqping that uses self-training HMM models and transcriptomic data. The pipeline processes the genome and transcriptome sequences of the target species using GlimmerHMM, SNAP, and AUGUSTUS pipelines, followed by MAKER2 program to combine predictions from the three tools in association with the transcriptomic evidence. Seqping generates species-specific HMMs that are able to offer unbiased gene predictions. The pipeline was evaluated using the Oryza sativa and Arabidopsis thaliana genomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis showed that the pipeline was able to identify at least 95% of BUSCO's plantae dataset. Our evaluation shows that Seqping was able to generate better gene predictions compared to three HMM-based programs (MAKER2, GlimmerHMM and AUGUSTUS) using their respective available HMMs. Seqping had the highest accuracy in rice (0.5648 for CDS, 0.4468 for exon, and 0.6695 nucleotide structure) and A. thaliana (0.5808 for CDS, 0.5955 for exon, and 0.8839 nucleotide structure).
CONCLUSIONS: Seqping provides researchers a seamless pipeline to train species-specific HMMs and predict genes in newly sequenced or less-studied genomes. We conclude that the Seqping pipeline predictions are more accurate than gene predictions using the other three approaches with the default or available HMMs.
Fulltext Side chain similarity comparisons for integrated drug repositioning and potential toxicity assessments in epidemic response scenarios: The case for COVID-19

Ab Ghani NS, Emrizal R, Makmur H, Firdaus-Raih M

Comput Struct Biotechnol J, 2020;18:2931-2944.
PMID: 33101604 DOI: 10.1016/j.csbj.2020.10.013

Structures of protein-drug-complexes provide an atomic level profile of drug-target interactions. In this work, the three-dimensional arrangements of amino acid side chains in known drug binding sites (substructures) were used to search for similarly arranged sites in SARS-CoV-2 protein structures in the Protein Data Bank for the potential repositioning of approved compounds. We were able to identify 22 target sites for the repositioning of 16 approved drug compounds as potential therapeutics for COVID-19. Using the same approach, we were also able to investigate the potentially promiscuous binding of the 16 compounds to off-target sites that could be implicated in toxicity and side effects that had not been provided by any previous studies. The investigations of binding properties in disease-related proteins derived from the comparison of amino acid substructure arrangements allows for effective mechanism driven decision making to rank and select only the compounds with the highest potential for success and safety to be prioritized for clinical trials or treatments. The intention of this work is not to explicitly identify candidate compounds but to present how an integrated drug repositioning and potential toxicity pipeline using side chain similarity searching algorithms are of great utility in epidemic scenarios involving novel pathogens. In the case of the COVID-19 pandemic caused by the SARS-CoV-2 virus, we demonstrate that the pipeline can identify candidate compounds quickly and sustainably in combination with associated risk factors derived from the analysis of potential off-target site binding by the compounds to be repurposed.
Fulltext Structural and functional analyses of Burkholderia pseudomallei BPSL1038 reveal a Cas-2/VapD nuclease sub-family

Shaibullah S, Shuhaimi N, Ker DS, Mohd-Sharif N, Ho KL, Teh AH, et al.

Commun Biol, 2023 Sep 08;6(1):920.
PMID: 37684342 DOI: 10.1038/s42003-023-05265-4

Burkholderia pseudomallei is a highly versatile pathogen with ~25% of its genome annotated to encode hypothetical proteins. One such hypothetical protein, BPSL1038, is conserved across seven bacterial genera and 654 Burkholderia spp. Here, we present a 1.55 Å resolution crystal structure of BPSL1038. The overall structure folded into a modified βαββαβα ferredoxin fold similar to known Cas2 nucleases. The Cas2 equivalent catalytic aspartate (D11) pairs are conserved in BPSL1038 although B. pseudomallei has no known CRISPR associated system. Functional analysis revealed that BPSL1038 is a nuclease with endonuclease activity towards double-stranded DNA. The DNase activity is divalent ion independent and optimum at pH 6. The concentration of monovalent ions (Na+ and K+) is crucial for nuclease activity. An active site with a unique D11(X20)SST motif was identified and proposed for BPSL1038 and its orthologs. Structure modelling indicates the catalytic role of the D11(X20)SST motif and that the arginine residues R10 and R30 may interact with the nucleic acid backbone. The structural similarity of BPSL1038 to Cas2 proteins suggests that BPSL1038 may represent a sub-family of nucleases that share a common ancestor with Cas2.
Structural dissection of two redox proteins from the shipworm symbiont Teredinibacter turnerae

Rajagopal BS, Yates N, Smith J, Paradisi A, Tétard-Jones C, Willats WGT, et al.

IUCrJ, 2024 Mar 01;11(Pt 2):260-274.
PMID: 38446458 DOI: 10.1107/S2052252524001386

The discovery of lytic polysaccharide monooxygenases (LPMOs), a family of copper-dependent enzymes that play a major role in polysaccharide degradation, has revealed the importance of oxidoreductases in the biological utilization of biomass. In fungi, a range of redox proteins have been implicated as working in harness with LPMOs to bring about polysaccharide oxidation. In bacteria, less is known about the interplay between redox proteins and LPMOs, or how the interaction between the two contributes to polysaccharide degradation. We therefore set out to characterize two previously unstudied proteins from the shipworm symbiont Teredinibacter turnerae that were initially identified by the presence of carbohydrate binding domains appended to uncharacterized domains with probable redox functions. Here, X-ray crystal structures of several domains from these proteins are presented together with initial efforts to characterize their functions. The analysis suggests that the target proteins are unlikely to function as LPMO electron donors, raising new questions as to the potential redox functions that these large extracellular multi-haem-containing c-type cytochromes may perform in these bacteria.
Fulltext The Glaciozyma antarctica genome reveals an array of systems that provide sustained responses towards temperature variations in a persistently cold habitat

Firdaus-Raih M, Hashim NHF, Bharudin I, Abu Bakar MF, Huang KK, Alias H, et al.

PLoS One, 2018;13(1):e0189947.
PMID: 29385175 DOI: 10.1371/journal.pone.0189947

Extremely low temperatures present various challenges to life that include ice formation and effects on metabolic capacity. Psyhcrophilic microorganisms typically have an array of mechanisms to enable survival in cold temperatures. In this study, we sequenced and analysed the genome of a psychrophilic yeast isolated in the Antarctic region, Glaciozyma antarctica. The genome annotation identified 7857 protein coding sequences. From the genome sequence analysis we were able to identify genes that encoded for proteins known to be associated with cold survival, in addition to annotating genes that are unique to G. antarctica. For genes that are known to be involved in cold adaptation such as anti-freeze proteins (AFPs), our gene expression analysis revealed that they were differentially transcribed over time and in response to different temperatures. This indicated the presence of an array of adaptation systems that can respond to a changing but persistent cold environment. We were also able to validate the activity of all the AFPs annotated where the recombinant AFPs demonstrated anti-freeze capacity. This work is an important foundation for further collective exploration into psychrophilic microbiology where among other potential, the genes unique to this species may represent a pool of novel mechanisms for cold survival.
Fulltext The genome of the Tiger Milk mushroom, Lignosus rhinocerotis, provides insights into the genetic basis of its medicinal properties

Yap HY, Chooi YH, Firdaus-Raih M, Fung SY, Ng ST, Tan CS, et al.

BMC Genomics, 2014;15:635.
PMID: 25073817 DOI: 10.1186/1471-2164-15-635

The sclerotium of Lignosus rhinocerotis (Cooke) Ryvarden or Tiger milk mushroom (Polyporales, Basidiomycota) is a valuable folk medicine for indigenous peoples in Southeast Asia. Despite the increasing interest in this ethnobotanical mushroom, very little is known about the molecular and genetic basis of its medicinal and nutraceutical properties.
Fulltext Transitioning from Soil to Host: Comparative Transcriptome Analysis Reveals the Burkholderia pseudomallei Response to Different Niches

Ghazali AK, Firdaus-Raih M, Uthaya Kumar A, Lee WK, Hoh CC, Nathan S

Microbiol Spectr, 2023 Mar 01;11(2):e0383522.
PMID: 36856434 DOI: 10.1128/spectrum.03835-22

Burkholderia pseudomallei, a soil and water saprophyte, is responsible for the tropical human disease melioidosis. A hundred years since its discovery, there is still much to learn about B. pseudomallei proteins that are essential for the bacterium's survival in and interaction with the infected host, as well as their roles within the bacterium's natural soil habitat. To address this gap, bacteria grown under conditions mimicking the soil environment were subjected to transcriptome sequencing (RNA-seq) analysis. A dual RNA-seq approach was used on total RNA from spleens isolated from a B. pseudomallei mouse infection model at 5 days postinfection. Under these conditions, a total of 1,434 bacterial genes were induced, with 959 induced in the soil environment and 475 induced in bacteria residing within the host. Genes encoding metabolism and transporter proteins were induced when the bacteria were present in soil, while virulence factors, metabolism, and bacterial defense mechanisms were upregulated during active infection of mice. On the other hand, capsular polysaccharide and quorum-sensing pathways were inhibited during infection. In addition to virulence factors, reactive oxygen species, heat shock proteins, siderophores, and secondary metabolites were also induced to assist bacterial adaptation and survival in the host. Overall, this study provides crucial insights into the transcriptome-level adaptations which facilitate infection by soil-dwelling B. pseudomallei. Targeting novel therapeutics toward B. pseudomallei proteins required for adaptation provides an alternative treatment strategy given its intrinsic antimicrobial resistance and the absence of a vaccine. IMPORTANCE Burkholderia pseudomallei, a soil-dwelling bacterium, is the causative agent of melioidosis, a fatal infectious disease of humans and animals. The bacterium has a large genome consisting of two chromosomes carrying genes that encode proteins with important roles for survival in diverse environments as well as in the infected host. While a general mechanism of pathogenesis has been proposed, it is not clear which proteins have major roles when the bacteria are in the soil and whether the same proteins are key to successful infection and spread. To address this question, we grew the bacteria in soil medium and then in infected mice. At 5 days postinfection, bacteria were recovered from infected mouse organs and their gene expression was compared against that of bacteria grown in soil medium. The analysis revealed a list of genes expressed under soil growth conditions and a different set of genes encoding proteins which may be important for survival, replication, and dissemination in an infected host. These proteins are a potential resource for understanding the full adaptation mechanism of this pathogen. In the absence of a vaccine for melioidosis and with treatment being reliant on combinatorial antibiotic therapy, these proteins may be ideal targets for designing antimicrobials to treat melioidosis.
Unravelling the adaptation strategies employed by Glaciozyma antarctica PI12 on Antarctic sea ice

Bharudin I, Abu Bakar MF, Hashim NHF, Mat Isa MN, Alias H, Firdaus-Raih M, et al.

Mar Environ Res, 2018 Jun;137:169-176.
PMID: 29598997 DOI: 10.1016/j.marenvres.2018.03.007

Glaciozyma antarctica PI12, is a psychrophilic yeast isolated from Antarctic sea. In this work, Expressed Sequence Tags (EST) from cells exposed to three different temperatures; 15 °C, 0 °C and -12 °C were generated to identify genes associated with cold adaptation. A total of 5376 clones from each library were randomly picked and sequenced. Comparative analyses from the resulting ESTs in each condition identified several groups of genes required for cold adaptation. Additionally, 319 unique transcripts that encoded uncharacterised functions were identified in the -12 °C library and are currently unique to G. antarctica. Gene expression analysis using RT-qPCR revealed two of the unknown genes to be up-regulated at -12 °C compared to 0 °C and 15 °C. These findings further contribute to the collective knowledge into G. antarctica cold adaptation and as a resource for understanding the ecological and physiological tolerance of psychrophilic microbes in general.

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