Recombinant Pelotomaculum thermopropionicum UPF0756 membrane protein PTH_1817 (PTH_1817)

What is PTH_1817 and what organism does it originate from?

PTH_1817 is a UPF0756 family membrane protein encoded by the gene PTH_1817 in Pelotomaculum thermopropionicum. P. thermopropionicum is a Gram-positive thermophilic bacterium that functions as a syntrophic organism in anaerobic biodegradation processes . The protein is classified as part of the UPF0756 protein family, which consists of uncharacterized membrane proteins with conserved domains but largely unknown function. The full-length protein consists of 146 amino acids and is typically studied in recombinant form with a His-tag for purification purposes .

What is the ecological significance of Pelotomaculum thermopropionicum in anaerobic environments?

Pelotomaculum thermopropionicum occupies a specialized ecological niche within anaerobic microbial communities. It functions as an intermediate organism in the sequential syntrophic catabolism of organic matter, specifically catalyzing the bottleneck step in anaerobic biodegradation. P. thermopropionicum converts volatile fatty acids (VFAs) and alcohols produced by upstream fermenting bacteria into acetate, hydrogen, and carbon dioxide, which serve as substrates for downstream methanogenic archaea .

The organism is particularly important in anaerobic biodegradation because of its ability to oxidize propionate under methanogenic conditions. Research indicates that a large fraction (>30%) of methane produced from complex organic matter in anaerobic environments is generated via propionate, highlighting the ecological significance of this organism . This positions P. thermopropionicum as a crucial link in the carbon flow within anaerobic environments.

What structural features of PTH_1817 suggest its function as a membrane protein?

The structural analysis of PTH_1817 reveals several features characteristic of integral membrane proteins. The amino acid sequence shows distinct hydrophobic regions with multiple stretches of hydrophobic residues (leucine, isoleucine, valine, and alanine), which likely form transmembrane helices . The presence of the sequence "MLVVLLLIGMAAHSSLIVIAACILLILKLTNVN" at the N-terminus suggests a signal peptide or initial transmembrane segment.

The protein contains charged and polar residues interspersed between hydrophobic regions, potentially forming extramembrane loops or domains that might be involved in interactions with other proteins or substrates. The clustering of aromatic residues (phenylalanine) at potential membrane-water interfaces is another structural feature consistent with membrane protein architecture. These structural characteristics align with its classification in the UPF0756 family of membrane proteins, though detailed structural studies using X-ray crystallography or cryo-EM would be necessary to confirm the exact arrangement of transmembrane domains .

How does the genomic context of PTH_1817 provide insights into its potential function?

The genomic context analysis of PTH_1817 provides valuable clues about its potential function in P. thermopropionicum. The gene is part of the 3,025,375-bp genome, which contains 2920 coding sequences (CDSs) distributed in a pattern that reflects the organism's ecological niche as a syntrophic specialist .

A distinctive feature of P. thermopropionicum's genome is that genes for important catabolic enzymes are physically linked to those encoding PAS-domain-containing regulators. This suggests that metabolic pathways, potentially including those involving PTH_1817, are regulated in response to environmental conditions rather than specific substrates . If PTH_1817 is located near genes involved in syntrophic metabolism or is co-regulated with such genes, this would suggest a potential role in the organism's primary ecological function.

The protein's classification as a UPF0756 family member and its conservation across syntrophic bacteria might indicate a specialized role in the unique metabolism of these organisms, potentially in membrane transport processes related to syntrophic growth or intercellular communication with methanogenic partners .

What is the evolutionary relationship between PTH_1817 and similar proteins in other syntrophic bacteria?

Evolutionary analysis suggests that PTH_1817 has evolved as part of the specialized adaptation of P. thermopropionicum to its syntrophic lifestyle. Comparative genomic analyses reveal that P. thermopropionicum shows close evolutionary relationships with other niche members in the anaerobic microbiota based on codon usage patterns, despite being phylogenetically distinct .

The genome of P. thermopropionicum contains unique features shared with Syntrophomonas wolfei, another syntrophic bacterium affiliated with Firmicutes. For example, both organisms possess 23S rRNA genes with two specific intervening sequences (IVS) that have high sequence similarity, providing evidence for their close evolutionary relationship . This suggests that proteins like PTH_1817 may have evolved specific functions that facilitate syntrophic metabolism through horizontal gene transfer or convergent evolution with other syntrophic specialists.

The evolutionary trajectory of PTH_1817 appears to have been shaped by the organism's interaction with other members of its ecological niche, particularly methanogens, rather than following strictly phylogenetic lines. This is evidenced by the finding that P. thermopropionicum is evolutionarily distant from phylogenetically related sugar-fermenting bacteria but shows similarities to its syntrophic partners .

What expression systems and purification strategies are most effective for producing recombinant PTH_1817?

For effective production of recombinant PTH_1817, expression in E. coli has been demonstrated to be successful. The recommended approach involves using a vector that allows for N-terminal His-tag fusion, which facilitates subsequent purification steps . When selecting an E. coli strain for expression, BL21(DE3) or similar strains designed for membrane protein expression may be optimal due to their reduced protease activity and controlled expression capabilities.

The purification protocol typically involves:

• Cell lysis under native conditions using sonication or pressure-based methods

• Membrane fraction isolation through differential centrifugation

• Solubilization of membrane proteins using appropriate detergents (e.g., n-dodecyl-β-D-maltoside or CHAPS)

• Immobilized metal affinity chromatography (IMAC) using Ni-NTA or similar matrices

• Size exclusion chromatography for further purification

The purified protein can be obtained with greater than 90% purity as determined by SDS-PAGE . Following purification, the protein is typically stored in a Tris/PBS-based buffer containing 6% trehalose at pH 8.0 to maintain stability .

What methods are recommended for reconstitution and storage of purified PTH_1817?

For optimal reconstitution and storage of purified PTH_1817, the following methodological approaches are recommended:

Reconstitution Protocol:

• Centrifuge the vial briefly before opening to bring contents to the bottom

• Reconstitute the lyophilized protein in deionized sterile water to a concentration of 0.1-1.0 mg/mL

• Add glycerol to a final concentration of 5-50% (50% is recommended as default)

• Aliquot the reconstituted protein for long-term storage

Storage Conditions:

• Store working aliquots at 4°C for up to one week

• For long-term storage, keep aliquots at -20°C or preferably -80°C

• Avoid repeated freeze-thaw cycles as this can compromise protein integrity

• For lyophilized protein, store at -20°C upon receipt

These recommendations are based on standard protocols for maintaining membrane protein stability while preventing aggregation and denaturation. The addition of trehalose in the storage buffer serves as a cryoprotectant that helps maintain protein structure during freeze-thaw cycles .

What analytical techniques are most appropriate for characterizing the structural features of PTH_1817?

For comprehensive structural characterization of PTH_1817, multiple complementary analytical techniques should be employed:

Membrane Protein Topology Analysis:

• Circular Dichroism (CD) Spectroscopy: To determine secondary structure composition (α-helices, β-sheets)

• Fluorescence Spectroscopy: Using intrinsic tryptophan fluorescence or extrinsic probes to assess tertiary structure

• FTIR Spectroscopy: To analyze secondary structure in membrane environments

Detailed Structural Determination:

• X-ray Crystallography: Requires successful crystallization of the protein, potentially facilitated by lipidic cubic phase methods

• Cryo-Electron Microscopy: Particularly useful for membrane proteins that resist crystallization

• NMR Spectroscopy: Solution NMR for smaller domains or solid-state NMR for the full-length protein in a membrane environment

Membrane Integration Analysis:

• Protease Protection Assays: To identify membrane-protected regions

• Site-Directed Spin Labeling: Combined with EPR spectroscopy to map membrane-embedded segments

• Molecular Dynamics Simulations: To predict membrane interactions and protein behavior in lipid bilayers

These techniques collectively provide insights into the three-dimensional structure, membrane topology, and potential functional domains of PTH_1817. The selection of methods depends on research objectives, available equipment, and the specific structural features being investigated .

What experimental approaches can determine the role of PTH_1817 in the syntrophic metabolism of P. thermopropionicum?

To investigate the role of PTH_1817 in syntrophic metabolism, several experimental approaches can be employed:

Genetic Manipulation Approaches:

• Gene Knockout/Knockdown Studies: Creating a PTH_1817 deletion mutant in P. thermopropionicum to observe phenotypic changes in syntrophic growth

• Complementation Studies: Reintroducing the wild-type or modified gene to confirm phenotype restoration

• Overexpression Analysis: Examining the effects of increased PTH_1817 expression on metabolic capabilities

Co-Culture Experiments:

• Syntrophic Growth Assays: Comparing wild-type and mutant strains in co-culture with methanogenic partners on various substrates

• Interspecies Electron Transfer Analysis: Measuring hydrogen or formate production/consumption rates in the presence/absence of PTH_1817

• Metabolic Flux Analysis: Using isotope-labeled substrates to track carbon flow through metabolic pathways

Molecular Interaction Studies:

• Protein-Protein Interaction Analysis: Using pull-down assays or bacterial two-hybrid systems to identify interaction partners

• Localization Studies: Employing fluorescent protein fusions to determine subcellular localization during syntrophic growth

• Transcriptomic Analysis: Comparing gene expression profiles under different growth conditions to identify co-regulated genes

These approaches would provide functional insights into PTH_1817's role in the context of P. thermopropionicum's ecological niche as a syntrophic specialist, potentially revealing involvement in membrane transport, signaling, or interspecies interactions that facilitate syntrophic metabolism .

How might the PAS-domain regulatory systems in P. thermopropionicum interact with membrane proteins like PTH_1817?

The potential interaction between PAS-domain regulatory systems and membrane proteins like PTH_1817 in P. thermopropionicum represents an important area for investigation. Genome analysis has revealed that P. thermopropionicum contains an unusually high number of signal transduction systems (165 one-component and 22 two-component systems) for its genome size, with PAS being the most frequently present input domain .

Potential Interaction Mechanisms:

• Direct Regulation: PAS-domain regulators might directly control PTH_1817 expression if the gene is located within a PAS-regulated operon. This would be consistent with the genomic organization of P. thermopropionicum, where genes for PAS domain-containing putative regulators are physically linked to those for important catabolic enzymes .

• Environmental Sensing: PAS domains typically sense environmental signals such as oxygen, light, or redox status. If PTH_1817 functions in a pathway affected by these conditions, its expression or activity might be modulated by PAS-containing regulators responding to environmental cues relevant to syntrophic metabolism.

• Metabolic Integration: The propionate-oxidizing methylmalonyl-CoA pathway, which forms the backbone of P. thermopropionicum's catabolic system, is regulated by a PAS-domain-containing regulator homologous to RocR . If PTH_1817 participates in related metabolic processes, it might be part of this regulatory network.

• Interspecies Communication: Given P. thermopropionicum's dependence on syntrophic partners, PAS-domain regulators might coordinate the expression of membrane proteins involved in interspecies electron transfer or metabolite exchange, potentially including PTH_1817.

Experimental approaches to investigate these interactions could include chromatin immunoprecipitation (ChIP) experiments, promoter activity assays under various conditions, and systematic analysis of gene expression patterns in response to different syntrophic partners or environmental conditions .

What comparative proteomic approaches would be most informative for understanding the functional context of PTH_1817?

To elucidate the functional context of PTH_1817, several comparative proteomic approaches would provide valuable insights:

Differential Expression Analysis:

• Quantitative Proteomics: Compare protein expression levels between different growth conditions (syntrophic vs. non-syntrophic, various substrates)

• Temporal Proteomics: Analyze protein expression changes during the establishment of syntrophic associations

• Spatial Proteomics: Examine membrane vs. cytosolic fractions to confirm localization and potential interaction partners

Protein-Protein Interaction Studies:

• Co-immunoprecipitation with Mass Spectrometry: Use anti-His antibodies to pull down PTH_1817 and identify co-precipitating proteins

• Proximity Labeling: Employ BioID or APEX2 fusions to identify proteins in close proximity to PTH_1817 in vivo

• Cross-linking Mass Spectrometry: Identify interaction interfaces through chemical cross-linking followed by MS analysis

Comparative Evolutionary Proteomics:

• Ortholog Analysis: Compare PTH_1817 with homologs in other syntrophic bacteria (e.g., Syntrophomonas wolfei) and non-syntrophic relatives

• Domain Conservation: Identify conserved protein domains and sequence motifs that might indicate function

• Co-evolution Analysis: Identify proteins that show similar evolutionary patterns to PTH_1817

Functional Proteomics:

• Activity-based Protein Profiling: Use chemical probes to identify proteins with specific activities

• Membrane Protein Complexome Analysis: Blue native PAGE combined with MS to identify native membrane protein complexes containing PTH_1817

• Phosphoproteomics: Determine if PTH_1817 undergoes post-translational modifications in response to changing conditions

These approaches would place PTH_1817 within its functional context, potentially revealing its role in the specialized metabolism of P. thermopropionicum as a syntrophic organism .

How should researchers interpret sequence homology data for PTH_1817 given its classification in the poorly characterized UPF0756 family?

Interpreting sequence homology data for proteins in poorly characterized families like UPF0756 requires careful consideration of multiple factors:

Homology Analysis Strategies:

• Beyond Simple BLAST Searches: Standard sequence similarity searches may yield limited information for poorly characterized families. Instead, researchers should employ:

  • Position-Specific Iterative BLAST (PSI-BLAST) to detect remote homologs

  • Hidden Markov Model (HMM) profiling using tools like HMMER

  • Sequence-structure threading approaches like I-TASSER or Phyre2

• Domain Architecture Analysis: Examine the arrangement of conserved domains within PTH_1817 and compare with other proteins:

  • Identify conserved motifs that might indicate function

  • Analyze the presence of transmembrane regions and their conservation

  • Look for patterns in extramembrane loop regions

• Phylogenetic Context Interpretation:

  • Examine the distribution of homologs across bacterial lineages

  • Pay special attention to conservation in other syntrophic bacteria

  • Compare with homologs in organisms with different metabolic capabilities

• Structural Prediction Integration:

  • Use structural predictions to identify potential binding sites or catalytic residues

  • Compare predicted structural elements with functionally characterized proteins

  • Focus on conserved residues in structurally important positions

• Genomic Context Analysis:

  • Examine neighboring genes in P. thermopropionicum and other organisms

  • Look for conserved gene clusters that might indicate functional relationships

  • Consider the correlation between the presence of PTH_1817 homologs and specific metabolic capabilities

By integrating these approaches, researchers can develop testable hypotheses about PTH_1817 function despite its classification in a poorly characterized protein family .

What bioinformatic approaches can predict membrane topology and functional domains in PTH_1817?

Predicting membrane topology and functional domains in PTH_1817 requires a multi-faceted bioinformatic approach:

Membrane Topology Prediction:

• Transmembrane Helix Prediction:

  • TMHMM, HMMTOP, and Phobius for basic transmembrane helix prediction

  • MEMSAT-SVM and TOPCONS for consensus-based predictions

  • DeepTMHMM or AlphaFold-Membrane for deep learning approaches

• Signal Peptide Analysis:

  • SignalP for signal peptide identification

  • PRED-TAT for twin-arginine translocation signal prediction

  • Distinguish between true signal peptides and first transmembrane segments

• Topology Orientation:

  • TOPCONS to predict inside/outside orientation of loops

  • Positive-inside rule validation

  • Charge bias analysis across predicted membrane segments

Functional Domain Prediction:

• Conserved Domain Analysis:

  • InterProScan for integrated domain searching

  • Pfam, SMART, and CDD for domain identification

  • CATH and SCOP for structural domain classification

• Functional Site Prediction:

  • ConSurf for evolutionary conservation mapping

  • 3DLigandSite for ligand binding site prediction

  • COACH for integrative function prediction

• Protein-Protein Interaction Surface Prediction:

  • SPPIDER for interaction site prediction

  • PrePPI for structure-based interaction prediction

  • PRISM for template-based interaction site identification

Integrated Approaches:

• Homology Modeling with Topology Constraints:

  • Generate structural models using AlphaFold or RoseTTAFold

  • Validate membrane orientation with PPM server

  • Refine models using molecular dynamics in membrane environments

• Evolutionary Coupling Analysis:

  • Use EVfold or RaptorX-Contact to identify co-evolving residues

  • Interpret contacts in the context of predicted topology

  • Identify potential functional networks within the protein

These bioinformatic approaches provide complementary information that, when integrated, can generate reliable predictions about the membrane topology and potential functional regions of PTH_1817 .

How can researchers design experiments to resolve contradictions between computational predictions and experimental data for PTH_1817?

When faced with contradictions between computational predictions and experimental data for proteins like PTH_1817, researchers should implement a systematic approach to resolution:

Experimental Validation Strategies:

• Site-Directed Mutagenesis Pipeline:

  • Design mutations targeting discrepant regions

  • Create a panel of variants with single and multiple mutations

  • Assess the impact on protein localization, stability, and function

  • Apply structure-function relationship analysis to refine computational models

• Topology Mapping Experiments:

  • Employ reporter fusion techniques (PhoA, GFP) at multiple positions

  • Use accessibility labeling with membrane-impermeable reagents

  • Implement limited proteolysis approaches to identify exposed regions

  • Compare results with computational predictions to identify discrepancies

• Structural Biology Approaches:

  • Use Hydrogen-Deuterium Exchange Mass Spectrometry (HDX-MS) to map solvent-accessible regions

  • Apply solid-state NMR to determine specific residue environments

  • Implement cryo-EM analysis of the protein in nanodiscs or liposomes

  • Compare experimental structures with computational predictions

Computational Refinement Strategies:

• Ensemble Prediction Approaches:

  • Generate predictions using multiple algorithms

  • Apply confidence scoring to identify regions of prediction uncertainty

  • Create consensus models weighted by algorithm performance

  • Highlight regions where predictions show high variance for targeted experimental validation

• Integrative Modeling:

  • Incorporate experimental constraints into computational models

  • Use Bayesian approaches to update predictions based on experimental data

  • Develop hybrid models that satisfy both computational and experimental constraints

  • Implement iterative refinement cycles

Resolution Framework:

• Systematic Comparison Matrix:

  • Create a detailed comparison of predictions vs. experimental results

  • Identify specific points of contradiction for focused investigation

  • Evaluate methodological limitations that might explain discrepancies

  • Develop testable hypotheses to resolve each contradiction

• Contextual Reevaluation:

  • Consider the influence of experimental conditions on protein behavior

  • Examine the impact of tags, fusion partners, or expression systems

  • Evaluate native vs. recombinant protein differences

  • Assess the role of lipid environment in membrane protein structure/function

By implementing this systematic approach, researchers can resolve contradictions between computational predictions and experimental data, leading to more accurate models of PTH_1817 structure and function .