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At least 613 records · Page 34

Functional Relevance of CASP16 Nucleic Acid Predictions as Evaluated by Structure Providers

ABSTRACT Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, experimental model building, and many other applications. Such algorithms to predict essential functional and structural features remain out of reach for biomolecular complexes containing nucleic acids. Here, we report a quantitative and qualitative evaluation of nucleic acid structures for the CASP16 blind prediction challenge by 12 of the experimental groups who provided nucleic acid targets. Blind predictions accurately model secondary structure and some aspects of tertiary structure, including reasonable global folds for some complex RNAs; however, predictions often lack accuracy in the regions of highest functional importance. All models have inaccuracies in non‐canonical regions where, for example, the nucleic‐acid backbone bends, deviating from an A‐form helix geometry, or a base forms a non‐standard hydrogen bond (not a Watson‐Crick base pair). These bends and non‐canonical interactions are integral to forming functionally important regions such as RNA enzymatic active sites. Additionally, the modeling of conserved and functional interfaces between nucleic acids and ligands, proteins, or other nucleic acids remains poor. For some targets, the experimental structures may not represent the only structure the biomolecular complex occupies in solution or in its functional life cycle, posing a future challenge for the community.

Biochemistry & Molecular Biology↗

Effective protein-protein interaction from structure factor data of a lysozyme solution

We report the determination of an effective protein-protein central potential for a lysozyme solution, obtained from the direct inversion of the total structure factor of the system, as extracted from small angle neutron scattering. The inversion scheme rests on a hypernetted-chain relationship between the effective potential and the structural functions, and is preliminarily tested for the case of a Lennard-Jones interaction. The characteristics of our potential are discussed in comparison with current models of effective interactions in complex fluids. The phase behavior predictions are also investigated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Force Field X: A computational microscope to study genetic variation and organic crystals using theory and experiment

Force Field X (FFX) is an open-source software package for atomic resolution modeling of genetic variants and organic crystals that leverages advanced potential energy functions and experimental data. FFX currently consists of nine modular packages with novel algorithms that include global optimization via a many-body expansion, acid–base chemistry using polarizable constant-pH molecular dynamics, estimation of free energy differences, generalized Kirkwood implicit solvent models, and many more. Applications of FFX focus on the use and development of a crystal structure prediction pipeline, biomolecular structure refinement against experimental datasets, and estimation of the thermodynamic effects of genetic variants on both proteins and nucleic acids. The use of Parallel Java and OpenMM combines to offer shared memory, message passing, and graphics processing unit parallelization for high performance simulations. Overall, the FFX platform serves as a computational microscope to study systems ranging from organic crystals to solvated biomolecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction and characterization of promoters and ribosomal binding sites of Zymomonas mobilis in system biology era

Zymomonas mobilis is a model bacterial ethanologen with many systems biology studies reported. Besides lignocellulosic ethanol production, Z. mobilis has been developed as a platform for biochemical production through metabolic engineering. However, identification and rigorous understanding of the genetic origins of cellular function, especially those based in non-coding region of DNA, such as promoters and ribosomal binding sites (RBSs), are still in its infancy. This knowledge is crucial for the effective application of Z. mobilis to new industrial applications of biotechnology for fuels and chemicals production. In this study, we explored the possibility to systematically predict the strength of promoters based on systems biology datasets. The promoter strength was clustered based on the expression values of downstream genes (or proteins) from systems biology studies including microarray, RNA-Seq and proteomics. Candidate promoters with different strengths were selected for further characterization, which include 19 strong, nine medium, and ten weak ones. A dual reporter-gene system was developed which included appropriate reporter genes. These are the opmCherry reporter gene driven by the constitutive PlacUV5 promoter for calibration, and EGFP reporter gene driven by candidate promoters for quantification. This dual reporter-gene system was confirmed using the inducible promoter, Ptet, which was used to determine the strength of these predicted promoters with different strengths. In addition, the dual reporter-gene system was applied to determine four synthetic RBSs with different translation initiation rates based on the prediction from bioinformatics server RBS calculator. Our results showed that the correlations between the prediction and experimental results for the promoter and RBS strength are relatively high, with R2 values more than 0.7 and 0.9, respectively. This study not only identified and characterized 38 promoters and four RBSs with different strengths for future metabolic engineering in Z. mobilis, but also established a flow cytometry-based dual reporter-gene system to characterize genetic elements including, but not limited to the promoters and RBSs studied in this work. This study also suggested the feasibility of predicting and selecting candidate genetic elements based on omics datasets and bioinformatics tools. Moreover, the dual reporter-gene system developed in this study can be utilized to characterize other genetic elements of Z. mobilis, which can also be applied to other microorganisms.

09 BIOMASS FUELS↗

Global Analysis of Photosynthesis Transcriptional Regulatory Networks

Photosynthesis is a crucial biological process that depends on the interplay of many components. This work analyzed the gene targets for 4 transcription factors: FnrL, PrrA, CrpK and MppG (RSP_2888), which are known or predicted to control photosynthesis in Rhodobacter sphaeroides. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) identified 52 operons under direct control of FnrL, illustrating its regulatory role in photosynthesis, iron homeostasis, nitrogen metabolism and regulation of sRNA synthesis. Using global gene expression analysis combined with ChIP-seq, we mapped the regulons of PrrA, CrpK and MppG. PrrA regulates ~34 operons encoding mainly photosynthesis and electron transport functions, while CrpK, a previously uncharacterized Crp-family protein, regulates genes involved in photosynthesis and maintenance of iron homeostasis. Furthermore, CrpK and FnrL share similar DNA binding determinants, possibly explaining our observation of the ability of CrpK to partially compensate for the growth defects of a ΔFnrL mutant. We show that the Rrf2 family protein, MppG, plays an important role in photopigment biosynthesis, as part of an incoherent feed-forward loop with PrrA. Our results reveal a previously unrealized, high degree of combinatorial regulation of photosynthetic genes and significant cross-talk between their transcriptional regulators, while illustrating previously unidentified links between photosynthesis and the maintenance of iron homeostasis.

59 BASIC BIOLOGICAL SCIENCES↗

The long non-coding RNA HOTAIR promotes the proliferation of serous ovarian cancer cells through the regulation of cell cycle arrest and apoptosis

HOX transcript antisense RNA (HOTAIR) is a well-known long non-coding RNA (lncRNA) whose dysregulation correlates with poor prognosis and malignant progression in many forms of cancer. Here, we investigate the expression pattern, clinical significance, and biological function of HOTAIR in serous ovarian cancer (SOC). Clinically, we found that HOTAIR levels were overexpressed in SOC tissues compared with normal controls and that HOTAIR overexpression was correlated with an advanced FIGO stage and a high histological grade. Multivariate analysis revealed that HOTAIR is an independent prognostic factor for predicting overall survival in SOC patients. We demonstrated that HOTAIR silencing inhibited A2780 and OVCA429 SOC cell proliferation in vitro and that the anti-proliferative effects of HOTAIR silencing also occurred in vivo. Further investigation into the mechanisms responsible for the growth inhibitory effects by HOTAIR silencing revealed that its knockdown resulted in the induction of cell cycle arrest and apoptosis through certain cell cycle-related and apoptosis-related proteins. Together, these results highlight a critical role of HOTAIR in SOC cell proliferation and contribute to a better understanding of the importance of dysregulated lncRNAs in SOC progression. - Highlights: • HOTAIR overexpression correlates with an aggressive tumour phenotype and a poor prognosis in SOC. • HOTAIR promotes SOC cell proliferation both in vitro and in vivo. • The proliferative role of HOTAIR is associated with regulation of the cell cycle and apoptosis.

60 APPLIED LIFE SCIENCES↗

Metallomics of two microorganisms relevant to heavy metal bioremediation reveal fundamental differences in metal assimilation and utilization

Although as many as half of all proteins are thought to require a metal cofactor, the metalloproteomes of microorganisms remain relatively unexplored. Microorganisms from different environments are likely to vary greatly in the metals that they assimilate, not just among the metals with well-characterized roles but also those lacking any known function. Herein we investigated the metal utilization of two microorganisms that were isolated from very similar environments and are of interest because of potential roles in the immobilization of heavy metals, such as uranium and chromium. The metals assimilated and their concentrations in the cytoplasm of Desulfovibrio vulgaris strain Hildenborough (DvH) and Enterobacter cloacae strain Hanford (EcH) varied dramatically, with a larger number of metals present in Enterobacter. For example, a total of 9 and 19 metals were assimilated into their cytoplasmic fractions, respectively, and DvH did not assimilate significant amounts of zinc or copper whereas EcH assimilated both. However, bioinformatic analysis of their genome sequences revealed a comparable number of predicted metalloproteins, 813 in DvH and 953 in EcH. These allowed some rationalization of the types of metal assimilated in some cases (Fe, Cu, Mo, W, V) but not in others (Zn, Nd, Ce, Pr, Dy, Hf and Th). It was also shown that U binds an unknown soluble protein in EcH but this incorporation was the result of extracellular U binding to cytoplasmic components after cell lysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Amino Acid Changes in Disease-Associated Variants Differ Radically from Variants Observed in the 1000 Genomes Project Dataset

The 1000 Genomes Project data provides a natural background dataset for amino acid germline mutations in humans. Since the direction of mutation is known, the amino acid exchange matrix generated from the observed nucleotide variants is asymmetric and the mutabilities of the different amino acids are very different. These differences predominantly reflect preferences for nucleotide mutations in the DNA (especially the high mutation rate of the CpG dinucleotide, which makes arginine mutability very much higher than other amino acids) rather than selection imposed by protein structure constraints, although there is evidence for the latter as well. The variants occur predominantly on the surface of proteins (82%), with a slight preference for sites which are more exposed and less well conserved than random. Mutations to functional residues occur about half as often as expected by chance. The disease-associated amino acid variant distributions in OMIM are radically different from those expected on the basis of the 1000 Genomes dataset. The disease-associated variants preferentially occur in more conserved sites, compared to 1000 Genomes mutations. Many of the amino acid exchange profiles appear to exhibit an anti-correlation, with common exchanges in one dataset being rare in the other. Disease-associated variants exhibit more extreme differences in amino acid size and hydrophobicity. More modelling of the mutational processes at the nucleotide level is needed, but these observations should contribute to an improved prediction of the effects of specific variants in humans.

59 BASIC BIOLOGICAL SCIENCES↗

Generative design of de novo proteins based on secondary-structure constraints using an attention-based diffusion model

We report two generative deep-learning models that predict amino acid sequences and 3D protein structures on the basis of secondary-structure design objectives via either the overall content or the per-residue structure. Both models are robust regarding imperfect inputs and offer de novo design capacity because they can discover new protein sequences not yet discovered from natural mechanisms or systems. The residue-level secondary-structure design model generally yields higher accuracy and more diverse sequences. These findings suggest unexplored opportunities for protein designs and functional outcomes within the vast amino acid sequences beyond known proteins. Our models, based on an attention-based diffusion model and trained on a dataset extracted from experimentally known 3D protein structures, offer numerous downstream applications in the conditional generative design of various biological or engineering systems. Future work could include additional conditioning and an exploration of other functional properties of the generated proteins for various properties beyond structural objectives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Carbon source–driven metabolic and regulatory remodeling defines phenomic states in Lipomyces starkeyi

Lipomyces is a genus of oleaginous yeasts with potential for contributing to reliable biomanufacturing supply chains. However, progress in advanced strain designs and engineering efforts are still constrained by a lack of understanding of the underlying molecular drivers of Lipomyces phenotypes. To address this gap, we collected a suite of multi-omic data to dissect how carbon source availability reshapes the metabolic network, lipid allocation, and regulatory architecture of Lipomyces starkeyi. We observed that glucose promotes biosynthetic and proliferative processes supported by abundant energy and carbon intermediates, xylose enhances redox-balancing mechanisms centered on the pentose phosphate pathway, and glycerol activates respiratory metabolism, ß-oxidation, and the glyoxylate cycle. Lipid species distributions remained consistent in both nitrogen replete and depleted conditions across the carbon sources, indicating robust production mechanisms. Regulatory protein identification and network analysis revealed glycerol-driven respiratory growth favors regulatory programs integrating stress tolerance, redox balance, and lipid-associated metabolism, whereas xylose growth activates compensatory transcriptional responses aimed at maintaining mitochondrial function. Nitrogen limitation modulates the strength of these responses but does not fundamentally alter their direction, reinforcing carbon source as the dominant driver of regulatory architecture. Taken together, this data enhances the understanding of Lipomyces molecular rearrangements and provides a foundation for further development of predictive phenotypic tools in this genus.

Biotechnology↗

Dissociative electron attachment to amide bond containing molecules: N-ethylformamide and N-ethylacetamide

To advance our quest to understand the role of low energy electrons in biomolecular systems, we performed investigations on dissociative electron attachment (DEA) to gas-phase N-ethylformamide (NEF) and N-ethylacetamide (NEA) molecules. Both molecules contain the amide bond, which is the linkage between two consecutive amino acid residues in proteins. Thus, their electron-induced dissociation can imitate the resonant behavior of the DEA process in more complex biostructures. Our experimental results indicate that in these two molecules, the dissociation of the amide bond results in a double resonant structure with peaks at ~5 eV and 9 eV. We also determined the energy position of resonant states for several negative ions, i.e., the other dissociation products from NEF and NEA. Our predictions of dissociation channels were supported by density functional theory calculations of the corresponding threshold energies. Our results and those previously reported for small amides and peptides imply the fundamental nature for breakage of the amide bond through the DEA process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Role of the signal sequence in proteorhodopsin biogenesis in E. coli

Blue-absorbing proteorhodopsin (BPR) from marine bacteria is a retinal-bound, light-activated, outwards proton transporter containing seven α-helical transmembrane segments (TMS). It is synthesized as a precursor species (pre-BPR) with a predicted N-terminal signal sequence that is cleaved to yield the mature protein. While optimizing the production of BPR in Escherichia coli to facilitate the construction of bioprotonic devices, we observed significant pre-BPR accumulation in the inner membrane and explored signal sequence requirements and export pathway. Here, we report that BPR does not rely on the Sec pathway for inner membrane integration, and that although it greatly enhances yields, its signal sequence is not necessary to obtain a functional product. We further show that an unprocessable version of pre-BPR obtained by mutagenesis of the signal peptidase I site exhibits all functional attributes of the wild-type protein and has the advantage of being produced at higher levels. Our results are consistent with the BPR signal sequence being recognized by the signal recognition particle (SRP; a protein that orchestrates the cotranslational biogenesis of inner membrane proteins) and serving as a beneficial “pro” domain rather than a traditional secretory peptide.

59 BASIC BIOLOGICAL SCIENCES↗

Genome Sequence of the Mesophilic Thermotogales Bacterium Mesotoga prima MesG1.Ag.4.2 Reveals the Largest Thermotogales Genome To Date

Here we describe the genome of Mesotoga prima MesG1.Ag4.2, the first genome of a mesophilic Thermotogales bacterium. Mesotoga prima was isolated from a polychlorinated biphenyl (PCB)-dechlorinating enrichment culture from Baltimore Harbor sediments. Its 2.97 Mb genome is considerably larger than any previously sequenced Thermotogales genomes, which range between 1.86 and 2.30 Mb. This larger size is due to both higher numbers of protein-coding genes and larger intergenic regions. In particular, the M. prima genome contains more genes for proteins involved in regulatory functions, for instance those involved in regulation of transcription. Together with its closest relative, Kosmotoga olearia, it also encodes different types of proteins involved in environmental and cell-cell interactions as compared with other Thermotogales bacteria. Amino acid composition analysis of M. prima proteins implies that this lineage has inhabited low-temperature environments for a long time. A large fraction of the M. prima genome has been acquired by lateral gene transfer (LGT): a DarkHorse analysis suggests that 766 (32%) of predicted protein-coding genes have been involved in LGT after Mesotoga diverged from the other Thermotogales lineages. A notable example of a lineage-specific LGT event is a reductive dehalogenase gene - a key enzyme in dehalorespiration, indicating M. prima may have a more active role in PCB dechlorination than was previously assumed.

59 BASIC BIOLOGICAL SCIENCES↗

Structure and proposed mechanism of α-glycerophosphate oxidase from Mycoplasma pneumoniae

In this study, the formation of hydrogen peroxide (H₂O₂) by the FAD-dependent α-glycerophosphate oxidase (GlpO), is important for the pathogenesis of Streptococcus pneumoniae and Mycoplasma pneumoniae . The structurally known GlpO from Streptococcus sp. ( Ssp GlpO) is similar to the pneumococcal protein ( Sp GlpO) and provides a guide for drug design against that target. However, M. pneumoniae GlpO ( Mp GlpO), having <20% sequence identity with structurally known GlpOs, appears to represent a second type of GlpO we designate as Type II GlpOs. Here, the recombinant His-tagged Mp GlpO structure is described at ~2.5 Å resolution, solved by molecular replacement using as a search model the Bordetella pertussis protein 3253 (Bp3253) a protein of unknown function solved by structural genomics efforts. Recombinant Mp GlpO is an active oxidase with a turnover number of ~580 min⁻¹ while Bp3253 showed no GlpO activity. No substantial differences exist between the oxidized and dithionite-reduced Mp GlpO structures. Although, no liganded structures were determined, a comparison with the tartrate-bound Bp3253 structure and consideration of residue conservation patterns guided the construction of a model for α-glycerophosphate (Glp) recognition and turnover by Mp GlpO. The predicted binding mode also appears relevant for the type I GlpOs (such as Ssp GlpO) despite differences in substrate recognition residues, and it implicates a histidine conserved in type I and II Glp oxidases and dehydrogenases as the catalytic acid/base. This work provides a solid foundation for guiding further studies of the mitochondrial Glp dehydrogenases as well as for continued studies of M. pneumoniae and S. pneumoniae glycerol metabolism and the development of novel therapeutics targeting Mp GlpO and Sp GlpO.

59 BASIC BIOLOGICAL SCIENCES↗

Gonadal transcriptomics elucidate patterns of adaptive evolution within marine rockfishes (Sebastes)

Background: The genetic mechanisms of speciation and adaptation in the marine environment are not well understood. The rockfish genus Sebastes provides a unique model system for studying adaptive evolution because of the extensive diversity found within this group, which includes morphology, ecology, and a broad range of life spans. Examples of adaptive radiations within marine ecosystems are considered an anomaly due to the absence of geographical barriers and the presence of gene flow. Using marine rockfishes, we identified signatures of natural selection from transcriptomes developed from gonadal tissue of two rockfish species (Sebastes goodei and S. saxicola). We predicted orthologous transcript pairs, and estimated their distributions of nonsynonymous (Ka) and synonymous (Ks) substitution rates. Results: We identified 144 genes out of 1079 orthologous pairs under positive selection, of which 11 are functionally annotated to reproduction based on gene ontologies (GOs). One orthologous pair of the zona pellucida gene family, which is known for its role in the selection of sperm by oocytes, out of ten was identified to be evolving under positive selection. In addition to our results in the protein coding-regions of transcripts, we found substitution rates in 3’ and 5’ UTRs to be significantly lower than Ks substitution rates implying negative selection in these regions. Conclusions: We were able to identify a series of candidate genes that are useful for the assessment of the critical genes that diverged and are responsible for the radiation within this genus. Genes associated with longevity hold potential for understanding the molecular mechanisms that have contributed to the radiation within this genus.

59 BASIC BIOLOGICAL SCIENCES↗

Design of Broadly Cross-Reactive M Protein–Based Group A Streptococcal Vaccines

Group A streptococcal infections are a significant cause of global morbidity and mortality. A leading vaccine candidate is the surface M protein, a major virulence determinant and protective Ag. An obstacle to the development of M protein–based vaccines is the >200 different M types defined by the N-terminal sequences that contain protective epitopes. Despite sequence variability, M proteins share coiled-coil structural motifs that bind host proteins required for virulence. In this study, we exploit this potential Achilles heel of conserved structure to predict cross-reactive M peptides that could serve as broadly protective vaccine Ags. Combining sequences with structural predictions, six heterologous M peptides in a sequence-related cluster were predicted to elicit cross-reactive Abs with the remaining five nonvaccine M types in the cluster. The six-valent vaccine elicited Abs in rabbits that reacted with all 11 M peptides in the cluster and functional opsonic Abs against vaccine and nonvaccine M types in the cluster. We next immunized mice with four sequence-unrelated M peptides predicted to contain different coiled-coil propensities and tested the antisera for cross-reactivity against 41 heterologous M peptides. Based on these results, we developed an improved algorithm to select cross-reactive peptide pairs using additional parameters of coiled-coil length and propensity. The revised algorithm accurately predicted cross-reactive Ab binding, improving the Matthews correlation coefficient from 0.42 to 0.74. These results form the basis for selecting the minimum number of N-terminal M peptides to include in potentially broadly efficacious multivalent vaccines that could impact the overall global burden of group A streptococcal diseases.

60 APPLIED LIFE SCIENCES↗

Assembly, Annotation, and Analysis of Multiple Mycorrhizal Fungal Genomes

Mycorrhizal fungi play critical roles in host plant health, soil community structure and chemistry, and carbon and nutrient cycling, all areas of intense interest to the US Dept. of Energy (DOE) Joint Genome Institute (JGI). To this end we are building on our earlier sequencing of the Laccaria bicolor genome by partnering with INRA-Nancy and the mycorrhizal research community in the MGI to sequence and analyze dozens of mycorrhizal genomes of all Basidiomycota and Ascomycota orders and multiple ecological types (ericoid, orchid, and ectomycorrhizal). JGI has developed and deployed high-throughput sequencing techniques, and Assembly, RNASeq, and Annotation Pipelines. In 2012 alone we sequenced, assembled, and annotated 12 draft or improved genomes of mycorrhizae, and predicted ~;;232831 genes and ~;;15011 multigene families, All of this data is publicly available on JGI MycoCosm (http://jgi.doe.gov/fungi/), which provides access to both the genome data and tools with which to analyze the data. Preliminary comparisons of the current total of 14 public mycorrhizal genomes suggest that 1) short secreted proteins potentially involved in symbiosis are more enriched in some orders than in others amongst the mycorrhizal Agaricomycetes, 2) there are wide ranges of numbers of genes involved in certain functional categories, such as signal transduction and post-translational modification, and 3) novel gene families are specific to some ecological types.

59 BASIC BIOLOGICAL SCIENCES↗

Transient local secondary structure in the intrinsically disordered C‐term of the Albino3 insertase

Albino3 (Alb3) is an integral membrane protein fundamental to the targeting and insertion of light‐harvesting complex (LHC) proteins into the thylakoid membrane. Alb3 contains a stroma‐exposed C‐terminus (Alb3‐Cterm) that is responsible for binding the LHC‐loaded transit complex before LHC membrane insertion. Alb3‐Cterm has been reported to be intrinsically disordered, but precise mechanistic details underlying how it recognizes and binds to the transit complex are lacking, and the functional roles of its four different motifs have been debated. Using a novel combination of experimental and computational techniques such as single‐molecule fluorescence resonance energy transfer, circular dichroism with deconvolution analysis, site‐directed mutagenesis, trypsin digestion assays, and all‐atom molecular dynamics simulations in conjunction with enhanced sampling techniques, we show that Alb3‐Cterm contains transient secondary structure in motifs I and II. The excellent agreement between the experimental and computational data provides a quantitatively consistent picture and allows us to identify a heterogeneous structural ensemble that highlights the local and transient nature of the secondary structure. This structural ensemble was used to predict both the inter‐residue distance distributions of single molecules and the apparent unfolding free energy of the transient secondary structure, which were both in excellent agreement with those determined experimentally. We hypothesize that this transient local secondary structure may play an important role in the recognition of Alb3‐Cterm for the LHC‐loaded transit complex, and these results should provide a framework to better understand protein targeting by the Alb3‐Oxa1‐YidC family of insertases.

Okoto, Patience S.↗