Mercury Methylation by HgcA: Theory Supports Carbanion Transfer to Hg(II)
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Zhou, Jing↗
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Machine learning sheds light on microbial dark proteins
In this article, metagenomics projects have revealed more than 8 billion non-redundant microbial protein sequences from across the Earth’s biosphere. Of these, 1.17 billion proteins do not have recognizable homologues in any of the more than 100,000 reference genomes available1. Understanding the function of these microbial proteins is a daunting task. Fortunately, machine learning has recently achieved unprecedented accuracy in modelling complex biological data and making predictions. At the forefront of these advancements are machine learning-based approaches that can confidently predict atomic-level protein structures for many (but not all) amino acid sequences.
59 BASIC BIOLOGICAL SCIENCES↗
Structures and Mechanisms of a Novel Bacterial Transport System for Fatty Acids
Abstract Bacterial acquisition of metabolites is largely facilitated by transporters with unique substrate scopes. The tripartite ATP‐independent periplasmic (TRAP) transporters comprise a large family of bacterial proteins that facilitate the uptake of a variety of small molecules. It has been reported that some TRAP systems encode a fourth protein, the T component. The T‐component, or TatT, is predicted to be a periplasmic‐facing lipoprotein that enables the uptake of metabolites from the outer membrane. However, no substrates were revealed for any TatT and their functional role(s) remained enigmatic. We recently identified a homolog in Methylococcus capsulatus that binds to sterols, and herein, we report two additional homologs that demonstrate a preference for long‐chain fatty acids. Our bioinformatics, quantitative analyses of protein‐ligand interactions, and high‐resolution crystal structures suggest that TatTs might facilitate the trafficking of hydrophobic or lipophilic substrates and represent a new class of bacterial lipid and fatty acid transporters.
59 BASIC BIOLOGICAL SCIENCES↗
Experimental Identification of Small Non-Coding RNAs in the Model Marine Bacterium Ruegeria pomeroyi DSS-3
In oligotrophic ocean waters where bacteria are often subjected to chronic nutrient limitation, community transcriptome sequencing has pointed to the presence of highly abundant small RNAs (sRNAs). The role of sRNAs in regulating response to nutrient stress was investigated in a model heterotrophic marine bacterium Ruegeria pomeroyi grown in continuous culture under carbon (C) and nitrogen (N) limitation. RNAseq analysis identified 99 putative sRNAs. Sixty-nine were cis-encoded and located antisense to a presumed target gene. Thirty were trans-encoded and initial target prediction was performed computationally. The most prevalent functional roles of genes anti-sense to the cis-sRNAs were transport, cell-cell interactions, signal transduction, and transcriptional regulation. Most sRNAs were transcribed equally under both C and N limitation, and may be involved in a general stress response. However, 14 were regulated differentially between the C and N treatments and may respond to specific nutrient limitations. A network analysis of the predicted target genes of the R. pomeroyi cis-sRNAs indicated that they average fewer connections than typical protein-encoding genes, and appear to be more important in peripheral or niche-defining functions encoded in the pan genome.
59 BASIC BIOLOGICAL SCIENCES↗
Genetic circuit design automation for yeast
Cells can be programmed to monitor and react to their environment using genetic circuits. Design automation software maps a desired circuit function to a DNA sequence, a process that requires units of gene regulation (gates) that are simple to connect and behave predictably. This poses a challenge for eukaryotes due to their complex mechanisms of transcription and translation. To this end, we have developed gates for yeast (Saccharomyces cerevisiae) that are connected using RNA polymerase flux as the signal carrier and are insulated from each other and host regulation. They are based on minimal constitutive promoters (~120 base pairs), for which rules are developed to insert operators for DNA-binding proteins. Using this approach, in this work we constructed nine NOT/NOR gates with nearly identical response functions and 400-fold dynamic range. In circuits, they are transcriptionally insulated from each other by placing ribozymes downstream of terminators to block nuclear export of messenger RNAs resulting from RNA polymerase readthrough. Based on these gates, Cello 2.0 was used to build circuits with up to 11 regulatory proteins. A simple dynamic model predicts the circuit response over days. Genetic circuit design automation for eukaryotes simplifies the construction of regulatory networks as part of cellular engineering projects, whether it be to stage processes during bioproduction, serve as environmental sentinels or guide living therapeutics.
59 BASIC BIOLOGICAL SCIENCES↗
Accurate prediction of protein structures and interactions using a three-track neural network
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track network in which information at the one-dimensional (1D) sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging x-ray crystallography and cryo–electron microscopy structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short-circuiting traditional approaches that require modeling of individual subunits followed by docking. Here, we make the method available to the scientific community to speed biological research.
59 BASIC BIOLOGICAL SCIENCES↗
Defining Lipidomic Responses to Coronavirus Infection
Highly pathogenic human coronavirus infection can cause a severe atypical, rapid onset pneumonia with a mortality rate of up to 10% for severe acute respiratory syndrome coronavirus 1 (SARS-CoV 1), 35% for Middle East respiratory syndrome coronavirus (MERS-CoV), or 1% for severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2 causative agent of COVID 19). While medical countermeasures successfully controlled the worldwide SARS-CoV epidemic, the MERS-CoV epidemic is still ongoing and continues to be a concern for travelers in the Middle East and the multi-year SARS-CoV 2 pandemic underscore the importance of defining biomarkers that are diagnostic and/or predictive of severe disease outcomes for respiratory viruses. Systems biology approaches provide global snapshots of infection induced changes in host cells/tissues and provide extremely rich datasets for understanding host pathogen interactions. Metabolites, especially lipids, are critical for viral replication but less is understood about infection induced changes to lipids due to limits in lipid species detection and identification. To characterize how individual lipid species and proteins with lipid associated functions contribute to highly pathogenic human coronavirus replication and disease severity, existing datasets were probed to determine cell type specific lipid responses to MERS-CoV infection and verification studies were performed to determine if modification of the host lipid signature (by inhibiting enzymatic functions that produce specific lipid species) can perturb CoV replication in human lung cells. MERS-CoV infects human lung epithelial, endothelial and fibroblast cells. All three cell types were infected with MERS-CoV and samples collected to analyze lipids, proteins, metabolites, and transcripts from 12 to 48 hours post infection. Time matched mock-infected cells were collected in parallel for each cell type. Following sample and statistical analysis, functional enrichment and bioinformatic analysis was performed to identify differentially expressed lipids and proteins. Two lipid species were found to be significantly upregulated following MERS-CoV infection, ceramides, and triacylglycerol both of which are indicative of cells undergoing apoptotic cell death. In contrast, sphingomyelins (lipid molecules that can serve as a precursor for one pathway for ceramide synthesis) had significantly decreased expression in MERS-CoV infected cells. An inhibitor of acid sphingomyelinase (that converts sphingomyelin to ceramides and phosphorylcholine) reduced MERS-CoV replication suggesting that production of ceramides is key for successful viral replication and transmission. Acyl-CoA-synthetase 3 (ACSL3), the only protein whose function is lipid associated and had increased differential expression in our dataset, regulates the synthesis of triacylglycerol (increased expression). Inhibitors that directly block ACSL3 (Triacsin C) but not steps later in the triacylglycerol synthesis pathway (Etomoxir) inhibit MERS-CoV replication suggesting that triacylglycerol production and/or ACSL3 activity is also key for viral replication. ACSL3 expression is also upregulated in lung cancer cells and is predicted to promote continued cell viability which would also enhance viral replication. The differentially expressed lipid and lipid-associated protein species identified in our studies suggest that MERS-CoV infection is activating cellular death pathways to limit the number of cells that become infected but also stimulating the production of lipid-associated enzymes that can prolong host cell viability and the amount of time progeny virions can be produced and released. As the inhibitors that worked against MERS-CoV infection were also efficacious against SARS-CoV 2 infection, countermeasures that target these host pathways may provide novel ways to block highly pathogenic human coronavirus infection and/or prevent severe disease outcomes.
59 BASIC BIOLOGICAL SCIENCES↗
Identification and Clinical Evaluation of Potential Biomarkers for Breast Cancer Resistance Protein ( BCRP / ABCG2 )
Clinical inhibition and genetic variation of the Breast Cancer Resistance Protein (BCRP/ABCG2) efflux transporter can significantly influence drug exposure, highlighting the need for reliable BCRP functional biomarkers. This study aimed to identify and evaluate biomarkers predictive of BCRP function in humans. A comprehensive analysis of metabolomic genome‐wide association studies (mGWAS) was conducted to discover potential BCRP biomarkers, followed by evaluation inin vitrotransporter assays and a clinical drug–drug interaction (DDI) study. Across multiple mGWAS datasets, plasma concentrations of three herbicide derivatives—4‐hydroxychlorothalonil (4HC), 3‐bromo‐5‐chloro‐2,6‐dihydroxybenzoic acid (BCDBA), and 3,5‐dichloro‐2,6‐dihydroxybenzoic acid (DCDBA)—were significantly elevated (P < 5E‐8) in individuals carrying reduced functionABCG2polymorphisms. These compounds were confirmed as novel BCRP substrates via transporter uptake assays and selected for clinical evaluation alongside riboflavin, a known BCRP substrate and potential BCRP biomarker. In a DDI study with 11 healthy subjects, eltrombopag, a BCRP inhibitor, increased rosuvastatin concentrations by approximately twofold (P = 0.002). No significant changes in the plasma concentrations of organic anion transporting polypeptide 1B (OATP1B) biomarkers (CP‐I and CP‐III) or potential BCRP biomarkers (4HC, BCDBA, DCDBA, or riboflavin) were observed. Notably, two subjects were heterozygous carriers for theABCG2p.Q141K variant and exhibited significantly higher baseline concentrations of 4HC (P = 0.004) and BCDBA (P = 0.0003), consistent with reduced BCRP function. These findings suggest that 4HC and BCDBA are promising biomarkers for baseline BCRP function in specific populations, such as those harboring reduced function genetic polymorphisms, but do not appear suitable for detecting acute BCRP inhibition.
Pharmacology & Pharmacy↗
SNHG16 contributes to breast cancer cell migration by competitively binding miR-98 with E2F5
Long noncoding RNAs (lncRNAs) have been proved to play important roles in cellular processes of cancer, including the development, proliferation, and migration of cancer cells. In the present study, we demonstrated small nucleolar RNA host gene 16 (SNHG16) as an oncogene on cell migration in breast cancer. Expression levels of SNHG16 were found to be frequently higher in breast cancer tissues than in the paired noncancerous tissues. Gain- and loss-of-function studies proved that SNHG16 significantly promoted breast cancer cell migration. We predicted SNHG16 as a competitive endogenous RNA (ceRNA) of E2F transcription factor 5 protein (E2F5) via competition for the shared miR-98 through bioinformatics analysis, and proved this regulation using relative quantitative real-time PCR (qRT-PCR), western blot, RNA immunoprecipitation (RIP) assay and luciferase reporter assay. In addition, we identified a positive correlation between SNHG16 and E2F5 in breast cancer tissues. Furthermore, we demonstrated that forced expression of miR-98 could partially abrogate SNHG16-mediated increase of breast cancer cells migration, suggesting that SNHG16 promoted cell migration in a miR-98 dependent manner. Taken together, our findings indicated that SNHG16 induces breast cancer cell migration by competitively binding miR-98 with E2F5, and SNHG16 can serve as a potential therapeutic target for breast cancer treatment. - Highlights: • SNHG16 was first shown to work as a ceRNA by competitively binding miR-98 with E2F5. • SNHG16 promotes breast cancer cell migration in a miR98-dependent manner. • Direct combination of SNHG16 with miR-98 was proved using RIP and luciferase assay. • The positive regulation of E2F5 by SNHG16 in breast cancer was revealed.
60 APPLIED LIFE SCIENCES↗
The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST)
In 2004, the SEED (http://pubseed.theseed.org/) was created to provide consistent and accurate genome annotations across thousands of genomes and as a platform for discovering and developing de novo annotations. The SEED is a constantly updated integration of genomic data with a genome database, web front end, API and server scripts. It is used by many scientists for predicting gene functions and discovering new pathways. In addition to being a powerful database for bioinformatics research, the SEED also houses subsystems (collections of functionally related protein families) and their derived FIGfams (protein families), which represent the core of the RAST annotation engine (http://rast. nmpdr.org/). When a new genome is submitted to RAST, genes are called and their annotations are made by comparison to the FIGfam collection. If the genome is made public, it is then housed within the SEED and its proteins populate the FIGfam collection. This annotation cycle has proven to be a robust and scalable solution to the problem of annotating the exponentially increasing number of genomes. To date, >12 000 users worldwide have annotated >60 000 distinct genomes using RAST. Here we describe the interconnectedness of the SEED database and RAST, the RAST annotation pipeline and updates to both resources.
59 BASIC BIOLOGICAL SCIENCES↗
Preparation and Characterization of the Extracellular Domain of Human Sid-1
In C. elegans, the cell surface protein Sid-1 imports extracellular dsRNA into the cytosol of most non-neuronal cells, enabling systemic spread of RNA interference (RNAi) throughout the worm. Sid-1 homologs are found in many other animals, although for most a function for the protein has not yet been established. Sid-1 proteins are composed of an N-terminal extracellular domain (ECD) followed by 9–12 predicted transmembrane regions. We developed a baculovirus system to express and purify the ECD of the human Sid-1 protein SidT1. Recombinant SidT1 ECD is glycosylated and spontaneously assembles into a stable and discrete tetrameric structure. Electron microscopy (EM) and small angle x-ray scattering (SAXS) studies reveal that the SidT1 ECD tetramer is a compact, puck-shaped globular particle, which we hypothesize may control access of dsRNA to the transmembrane pore. These characterizations provide inroads towards understanding the mechanism of this unique RNA transport system from structural prospective.
59 BASIC BIOLOGICAL SCIENCES↗
Subfamily-specific adaptations in the structures of two penicillin-binding proteins from Mycobacterium tuberculosis
Beta-lactam antibiotics target penicillin-binding proteins including several enzyme classes essential for bacterial cell-wall homeostasis. To better understand the functional and inhibitor-binding specificities of penicillin-binding proteins from the pathogen, Mycobacterium tuberculosis , we carried out structural and phylogenetic analysis of two predicted D,D-carboxypeptidases, Rv2911 and Rv3330. Optimization of Rv2911 for crystallization using directed evolution and the GFP folding reporter method yielded a soluble quadruple mutant. Structures of optimized Rv2911 bound to phenylmethylsulfonyl fluoride and Rv3330 bound to meropenem show that, in contrast to the nonspecific inhibitor, meropenem forms an extended interaction with the enzyme along a conserved surface. Phylogenetic analysis shows that Rv2911 and Rv3330 belong to different clades that emerged in Actinobacteria and are not represented in model organisms such as Escherichia coli and Bacillus subtilis . Clade-specific adaptations allow these enzymes to fulfill distinct physiological roles despite strict conservation of core catalytic residues. The characteristic differences include potential protein-protein interaction surfaces and specificity-determining residues surrounding the catalytic site. Overall, these structural insights lay the groundwork to develop improved beta-lactam therapeutics for tuberculosis.
59 BASIC BIOLOGICAL SCIENCES↗
Simple biochemical features underlie transcriptional activation domain diversity and dynamic, fuzzy binding to Mediator
Gene activator proteins comprise distinct DNA-binding and transcriptional activation domains (ADs). Because few ADs have been described, we tested domains tiling all yeast transcription factors for activation in vivo and identified 150 ADs. By mRNA display, we showed that 73% of ADs bound the Med15 subunit of Mediator, and that binding strength was correlated with activation. AD-Mediator interaction in vitro was unaffected by a large excess of free activator protein, pointing to a dynamic mechanism of interaction. Structural modeling showed that ADs interact with Med15 without shape complementarity (‘fuzzy’ binding). ADs shared no sequence motifs, but mutagenesis revealed biochemical and structural constraints. Finally, a neural network trained on AD sequences accurately predicted ADs in human proteins and in other yeast proteins, including chromosomal proteins and chromatin remodeling complexes. These findings solve the longstanding enigma of AD structure and function and provide a rationale for their role in biology.
60 APPLIED LIFE SCIENCES↗
Deep Green Unannotated Protein Structures
The Deep Green list is based on the identification and curation of conserved unannotated proteins in three green lineage (Viridiplantae) model organisms; Arabidopsis thaliana, Chlamydomonas reinhardtii, and Setaria viridis. Preliminary characterization of Deep Green proteins and genes was done using various informatics tools and published data sets and is presented in Knoshaug, Sun, et al., 2023, submitted. The structures of these unannotated proteins were also predicted using AlphaFold (Jumper et al., 2021). The data deposited here are the AlphaFold structural predictions having the highest pLDDT score and thus identified as the best folded structure (ranked_0). These data enable others to do in-depth structural characterizations to aid in functional characterization leading to deeper understanding of plant biology. References: Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., Bridgland, A., Meyer, C., Kohl, S. A. A., Ballard, A. J., Cowie, A., Romera-Paredes, B., Nikolov, S., Jain, R., Adler, J., Back, T., Petersen, S., Reiman, D., Clancy, E., Zielinski, M., Steinegger, M., Pacholska, M., Berghammer, T., Bodenstein, S., Silver, D., Vinyals, O., Senior, A. W., Kavukcuoglu, K., Kohli, P. and Hassabis, D. (2021) Highly accurate protein structure prediction with AlphaFold. Nature, 596:583-589. Knoshaug, E. P., Sun, P., Nag, A., Nguyen, H., Mattoon, E. M., Zhang, N., Liu, J., Chen, C., Cheng, J., Zhang, R., St. John, P., and Umen, J. (submitted) Identification and preliminary characterization of conserved uncharacterized proteins from Chlamydomonas reinhardtii, Arabidopsis thaliana, and Setaria viridis.
09 BIOMASS FUELS↗
MiR-107 suppresses proliferation of hepatoma cells through targeting HMGA2 mRNA 3′UTR
Background and aim: Aberrant expression of miR-107 is involved in the development of several human cancers. However, the role of miR-107 in hepatocellular carcinoma (HCC) is not well documented. In the present study, we aim to explore the function of miR-107 in hepatocarcinogenesis. Methods: Bioinformatics analysis was applied to predict the target genes of miR-107. Luciferase reporter gene assay was performed to verify the miR-107 binding sites in 3′-untranslated region (3′UTR) of high mobility group A2 (HMGA2) mRNA. The expression levels of mRNA and protein were examined using qRT-PCR and Western blot analysis. Functionally, MTT and EdU assays were carried out for proliferation analysis. Clinically, thirty HCC samples and their corresponding peritumor liver tissues were collected. Results: Bioinformatics analysis revealed that miR-107 might target HMGA2 mRNA 3′UTR. Luciferase reporter gene assays verified that the miR-107 binding site was located in the 3′UTR of HMGA2 mRNA. Furthermore, miR-107 could down-regulate HMGA2 at the levels of mRNA and protein in a dose-dependent manner. Interestingly, miR-107 inhibited the proliferation of hepatoma cells, while anti-miR-107 could promote the cell proliferation, which was blocked by the interference of HMGA2. Clinically, miR-107 was lower in HCC samples relative to peritumor liver tissues. The expression levels of miR-107 were negatively correlated with those of HMGA2 mRNA in HCC samples. Conclusion: MiR-107 suppresses the proliferation of hepatoma cells by targeting HMGA2 mRNA. Our finding provides new insights into the mechanism of hepatocarcinogenesis. - Highlights: • HMGA2 is a novel target gene of miR-107. • MiR-107 suppresses the proliferation of HCC cells through targeting HMGA2 mRNA. • MiR-107 is decreased in clinical HCC tissues. • MiR-107 is negatively correlated with HMGA2 in clinical HCC tissues.
60 APPLIED LIFE SCIENCES↗
SPARCL1 Expression Increases With Preoperative Radiation Therapy and Predicts Better Survival in Rectal Cancer Patients
Purpose: The secreted protein acidic and rich in cysteine-like 1 (SPARCL1) is expressed in various normal tissues and many types of cancers. The function of SPARCL1 and its relationship to a patient's prognosis have been studied, whereas its relationship to radiation therapy (RT) is not known. Our aim was to investigate the expression of SPARCL1 in rectal cancer patients who participated in a clinical trial of preoperative RT. Methods and Materials: The study included 136 rectal cancer patients who were randomized to undergo preoperative RT and surgery (n=63) or surgery alone (n=73). The expression levels of SPARCL1 in normal mucosa (n=29), primary tumor (n=136), and lymph node metastasis (n=35) were determined by immunohistochemistry. Results: Tumors with RT had stronger SPARCL1 expression than tumors without RT (P=.003). In the RT group, strong SPARCL1 expression was related to better survival than weak expression in patients with stage III tumors, independent of sex, age, differentiation, and margin status (P=.022; RR = 18.128; 95% confidence interval, 1.512-217.413). No such relationship was found in the non-RT group (P=.224). Further analysis of interactions among SPARCL1 expression, RT, and survival showed statistical significance (P=.024). In patients with metastases who received RT, strong SPARCL1 expression was related to better survival compared to weak expression (P=.041) but not in the non-RT group (P=.569). Conclusions: SPARCL1 expression increases with RT and is related to better prognosis in rectal cancer patients with RT but not in patients without RT. This result may help us to select the patients best suited for preoperative RT.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
The crystal structure of Grindelia robusta 7,13-copalyl diphosphate synthase reveals active site features controlling catalytic specificity
Diterpenoid natural products serve critical functions in plant development and ecological adaptation and many diterpenoids have economic value as bioproducts. The family of class II diterpene synthases catalyzes the committed reactions in diterpenoid biosynthesis, converting a common geranylgeranyl diphosphate precursor into different bicyclic prenyl diphosphate scaffolds. Enzymatic rearrangement and modification of these precursors generate the diversity of bioactive diterpenoids. We report the crystal structure of Grindelia robusta 7,13-copalyl diphosphate synthase, GrTPS2, at 2.1 Å of resolution. GrTPS2 catalyzes the committed reaction in the biosynthesis of grindelic acid, which represents the signature metabolite in species of gumweed (Grindelia spp., Asteraceae). Grindelic acid has been explored as a potential source for drug leads and biofuel production. The GrTPS2 crystal structure adopts the conserved three-domain fold of class II diterpene synthases featuring a functional active site in the γβ-domain and a vestigial α-domain. Substrate docking into the active site of the GrTPS2 apo protein structure predicted catalytic amino acids. Biochemical characterization of protein variants identified residues with impact on enzyme activity and catalytic specificity. Specifically, mutagenesis of Y457 provided mechanistic insight into the position-specific deprotonation of the intermediary carbocation to form the characteristic 7,13 double bond of 7,13-copalyl diphosphate.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Probing a Silent Metal: A Combined X-ray Absorption and Emission Spectroscopic Study of Biologically Relevant Zinc Complexes
As the second most common transition metal in the human body, Zinc is of great interest in research but has few viable routes for its direct structural study in biological systems. Herein, Zn valence-to-core X-ray emission spectroscopy (VtC XES) and Zn K-edge X-ray absorption spectroscopy (XAS) are presented as a means to understand the local structure of zinc in biological systems through the application of these methods to a series of biologically relevant model complexes. Taken together, the Zn K-edge XAS and VtC XES provide a means to establish the ligand identity, local geometry, and metal-ligand bond lengths. Experimental results were supported by strongly correlated density-functional-theory-based calculations, which, coupled with the complementarity of the two spectroscopic approaches, further enables future applications to protein systems to be examined in a predictive fashion. In this regard, test calculations were performed to showcase the sensitivity of these techniques to realistic biological applications.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗