Inflammation: Upregulated 5-fold in intestinal epithelial cells (Caco-2, HCEC-1CT) under IFNγ stimulation .
Conservation: Shares conserved regions with chimpanzee homologs, suggesting evolutionary importance .
Genetic association: Proximity to genome-wide significant SNPs (e.g., rs61827877) in hypertension studies .
In vitro studies: Used to investigate:
Biochemical tools: Commercial availability from multiple vendors (Cusabio, Creative BioMart, Gentaur) .
Functional ambiguity: Classified as "uncharacterized" due to lack of enzymatic or structural data .
Regulatory complexity: Co-expressed with IRF1-AS1 lncRNA, complicating functional isolation .
Recombinant Human Putative uncharacterized protein C1orf98 (C1orf98) is a protein with currently unknown function that has been identified in the human genome. It is also known by the target name LINC00862 in some databases . The significance of studying uncharacterized proteins like C1orf98 lies in their potential to reveal novel cellular mechanisms, pathways, or functions that could be important for understanding human biology and disease.
Uncharacterized proteins represent significant gaps in our knowledge of the human proteome. By studying these proteins systematically, researchers contribute to completing our understanding of cellular processes. Similar to the approach used with C17orf80 (another uncharacterized protein), research on C1orf98 may eventually reveal unexpected associations with critical cellular structures or functions .
Based on available data, C1orf98 is identified in the UniProt database with the accession number A6NCI5 . The commercially available recombinant form is produced in mammalian cells and has a purity of >85% as determined by SDS-PAGE analysis . The protein is available in partial length rather than full-length form .
For researchers interested in C1orf98's biochemical properties, standard analytical techniques should be employed:
Size determination through gel filtration chromatography
Secondary structure analysis through circular dichroism
Stability assessment through thermal shift assays
Post-translational modification analysis through mass spectrometry
These basic characterizations provide the foundation for more advanced functional studies.
Initial characterization experiments should follow a systematic approach:
Expression analysis: Determine tissue distribution and expression levels of endogenous C1orf98 using RT-qPCR and western blotting
Subcellular localization: Perform immunofluorescence microscopy and subcellular fractionation, similar to techniques used for C17orf80 localization
Sequence analysis: Conduct bioinformatic analysis to identify conserved domains, motifs, or sequence similarities with characterized proteins
Interaction studies: Perform pull-down assays and co-immunoprecipitation to identify binding partners
Table 1: Recommended Initial Characterization Experiments for C1orf98
| Experimental Approach | Purpose | Expected Outcome | Controls Required |
|---|---|---|---|
| RT-qPCR | Tissue expression profiling | Expression pattern across tissues | Housekeeping genes (GAPDH, β-actin) |
| Immunofluorescence | Subcellular localization | Cellular compartment identification | Known markers for subcellular compartments |
| Bioinformatic analysis | Domain/motif prediction | Potential functional elements | Validated proteins with similar features |
| Co-immunoprecipitation | Protein-protein interaction | Identification of binding partners | IgG control, input lysate |
When designing experiments to determine C1orf98 function, employ true experimental research design principles with proper controls and randomization:
Clearly define variables: Identify independent variables (e.g., presence/absence of C1orf98, expression levels) and dependent variables (e.g., cellular phenotypes, molecular readouts)
Establish control groups: Include appropriate negative controls (e.g., non-targeting siRNA) and positive controls (e.g., siRNA targeting a gene with known phenotype)
Randomize samples: Ensure random distribution of experimental units to minimize bias
Control extraneous variables: Standardize experimental conditions to isolate the effect of C1orf98 manipulation
For knockdown/knockout experiments:
Use multiple siRNAs/sgRNAs targeting different regions of C1orf98
Validate knockdown/knockout efficiency at protein and mRNA levels
Perform rescue experiments by re-expressing siRNA-resistant C1orf98 constructs
These approaches will help establish causality between C1orf98 and observed phenotypes, adhering to true experimental design principles .
For investigating protein-protein interactions involving C1orf98:
Affinity purification coupled with mass spectrometry (AP-MS):
Express tagged C1orf98 (e.g., FLAG, HA, or BioID) in relevant cell lines
Perform pull-down experiments followed by mass spectrometry
Compare with control samples to identify specific interactors
Proximity labeling approaches:
Co-immunoprecipitation with candidate interactors:
Based on bioinformatics predictions or preliminary screens
Validate using both overexpressed and endogenous proteins
Yeast two-hybrid screening:
Use C1orf98 as bait to screen against human cDNA libraries
Validate hits with orthogonal methods
These interaction studies should be performed under different cellular conditions (e.g., stress, different growth phases) to identify context-dependent interactions.
When facing conflicting experimental results with C1orf98:
Systematically evaluate methodology differences:
Examine protein preparation methods (recombinant vs. endogenous)
Compare cell types or tissues used across studies
Assess differences in experimental conditions or reagents
Conduct dose-response studies:
Test multiple concentrations or expression levels of C1orf98
Evaluate if effects are concentration-dependent or exhibit thresholds
Temporal analysis:
Investigate if contradictory results might be due to time-dependent effects
Perform time-course experiments to capture dynamic processes
Multi-method validation:
Apply orthogonal techniques to validate findings
For example, complement microscopy with biochemical fractionation
Statistical reassessment:
Increase sample sizes to enhance statistical power
Implement more rigorous statistical analyses, including testing for outliers
Remember that contradictions can reveal important biological nuances and should be thoroughly investigated rather than dismissed.
The optimal storage conditions for C1orf98 depend on its formulation :
Lyophilized form:
Store at -20°C or -80°C
Expected shelf life: approximately 12 months
Protect from moisture and avoid repeated freeze-thaw cycles
Liquid form:
Store at -20°C or -80°C
Expected shelf life: approximately 6 months
Aliquot to minimize freeze-thaw cycles
Working aliquots:
The stability of the protein is influenced by buffer composition, storage temperature, and the intrinsic properties of the protein itself . For long-term experiments, it's advisable to establish activity benchmarks at the beginning of the study to monitor potential degradation over time.
For reconstituting C1orf98:
Initial preparation:
Reconstitution procedure:
Stabilization with glycerol:
Aliquoting:
Prepare small single-use aliquots to avoid repeated freeze-thaw cycles
Label clearly with concentration, date, and buffer composition
This protocol maximizes protein stability and minimizes degradation during experimental workflows.
Determining the subcellular localization of C1orf98 requires a multi-method approach:
Fluorescence microscopy techniques:
Immunofluorescence using validated antibodies against endogenous C1orf98
Expression of fluorescently tagged C1orf98 (with careful validation that tagging doesn't affect localization)
Co-localization with known organelle markers
Biochemical fractionation:
Differential centrifugation to separate subcellular compartments
Western blotting of fractions to detect C1orf98
Comparison with known compartment markers (e.g., GAPDH for cytosol, Lamin A/C for nucleus)
Proximity labeling approaches:
Table 2: Subcellular Localization Methods Comparison
| Method | Advantages | Limitations | Controls Required |
|---|---|---|---|
| Immunofluorescence | Direct visualization, co-localization capability | Antibody specificity concerns | Knockdown/knockout cells, blocking peptides |
| Fluorescent protein fusion | Live cell imaging possible, no antibody needed | Tag may affect localization | Multiple tag positions (N- and C-terminal) |
| Subcellular fractionation | Quantitative, biochemical validation | Limited resolution, contamination between fractions | Compartment-specific markers |
| Proximity labeling | Identifies neighboring proteins, works with transient interactions | Requires genetic manipulation | Non-targeting fusion constructs |
Designing CRISPR-Cas9 experiments for C1orf98 functional studies:
Guide RNA design:
Design 3-4 sgRNAs targeting different exons of the C1orf98 gene
Focus on early exons to maximize disruption of protein function
Check for off-target effects using prediction algorithms
Consider the PAM site accessibility in the genomic context
Knockout validation strategies:
Genomic validation: T7 endonuclease assay, Sanger sequencing of the targeted region
Transcript validation: RT-PCR and qPCR with primers spanning the targeted region
Protein validation: Western blotting with validated antibodies
Phenotypic analysis pipeline:
Start with broad screens (viability, proliferation, morphology)
Progress to more specific assays based on bioinformatic predictions
Compare with phenotypes of related genes or pathways
Rescue experiments:
Re-express wild-type C1orf98 to confirm specificity of observed phenotypes
Create domain mutants to identify functional regions
Use inducible systems to study temporal aspects of phenotypes
Controls:
Non-targeting sgRNA controls
Knockout of genes with known phenotypes as positive controls
Isogenic cell lines differing only in C1orf98 status
These approaches follow true experimental design principles by manipulating independent variables (C1orf98 presence/function) while controlling for confounding factors .
To identify molecular functions of C1orf98:
Integrated bioinformatics analysis:
Sequence-based predictions: conservation analysis, domain prediction, structural modeling
Expression correlation analysis: identification of genes with similar expression patterns
Network-based approaches: incorporation into protein-protein interaction networks
Omics-based functional profiling:
Transcriptomics: RNA-seq after knockdown/overexpression to identify affected pathways
Proteomics: Global proteome changes and post-translational modification alterations
Metabolomics: Changes in metabolite profiles to infer biochemical influences
Biochemical activity screening:
Enzymatic activity assays based on predicted domains
DNA/RNA binding assays if predicted to interact with nucleic acids
Lipid binding assays if predicted to interact with cellular membranes
Genetic interaction mapping:
CRISPR screening to identify synthetic lethal or synthetic viable interactions
Double knockdown/knockout studies with predicted pathway components
Suppressor screens to identify genes that rescue C1orf98 loss phenotypes
This multi-faceted approach has proven successful for characterizing previously uncharacterized proteins like C17orf80, which was found to associate with mitochondrial membranes and nucleoids .
Given that some uncharacterized proteins like C17orf80 have been found to interact with nucleic acids (mitochondrial DNA) and membranes , similar investigations for C1orf98 are warranted:
Nucleic acid interaction studies:
Electrophoretic mobility shift assays (EMSA) with various DNA/RNA substrates
Chromatin immunoprecipitation (ChIP) or RNA immunoprecipitation (RIP)
DNase/RNase treatment followed by co-immunoprecipitation to determine if interactions are nucleic acid-dependent
CLIP-seq or similar technologies to identify binding sites if RNA interaction is suspected
Membrane association studies:
Membrane flotation assays to determine if C1orf98 associates with membranes
Protease protection assays to determine topology
Detergent resistance assays to characterize membrane microdomain association
FRAP (fluorescence recovery after photobleaching) to assess membrane dynamics
Experimental design considerations:
Include appropriate controls (known DNA/RNA binding proteins, known membrane proteins)
Test multiple conditions (salt concentration, pH) to identify interaction requirements
Consider post-translational modifications that might regulate these interactions
These approaches should incorporate true experimental design principles by systematically manipulating variables and including appropriate controls .
Expression and purification of recombinant proteins, especially uncharacterized ones like C1orf98, often present technical challenges:
Expression optimization:
Solubility enhancement strategies:
Fusion tags: MBP, GST, SUMO, or TRX to increase solubility
Co-expression with chaperones
Expression at lower temperatures
Inclusion of specific additives in lysis buffer
Purification optimization:
Multi-step purification strategy (e.g., affinity chromatography followed by size exclusion)
Screen different buffer conditions (pH, salt, additives)
Consider on-column refolding for proteins expressed in inclusion bodies
Stability enhancement:
Table 3: Troubleshooting Guide for C1orf98 Expression and Purification
| Challenge | Potential Causes | Solutions | Validation Method |
|---|---|---|---|
| Low expression levels | Codon bias, toxicity, mRNA instability | Codon optimization, inducible systems, alternate cell lines | Western blot, qPCR |
| Poor solubility | Hydrophobic regions, improper folding | Fusion tags, detergents, co-expression with partners | Solubility fractionation |
| Aggregation during purification | Concentration-dependent effects, buffer incompatibility | Screen buffers, gradual dialysis, reduced concentration | Dynamic light scattering |
| Loss of activity | Denaturation, co-factor loss, proteolysis | Stabilizing additives, protease inhibitors, native purification | Activity assays |
Post-translational modifications (PTMs) often regulate protein function and can be crucial for understanding uncharacterized proteins:
Computational prediction:
Use algorithms to predict potential PTM sites (phosphorylation, glycosylation, ubiquitination)
Compare predictions across species to identify conserved modification sites
Mass spectrometry-based approaches:
Enrichment strategies for specific PTMs:
Phosphorylation: TiO2 or IMAC enrichment
Ubiquitination: di-Gly antibody pulldown
Glycosylation: lectin affinity or hydrazide chemistry
Targeted and untargeted MS approaches
Quantitative comparison across different cellular conditions
Site-directed mutagenesis validation:
Mutate predicted PTM sites to non-modifiable residues
Create phosphomimetic mutations (e.g., Ser to Asp/Glu)
Assess functional consequences through phenotypic assays
PTM-specific antibodies:
When available, use modification-specific antibodies
Western blotting under different cellular conditions
Immunoprecipitation followed by mass spectrometry
These approaches follow experimental design principles by manipulating variables (cellular conditions, mutation of modification sites) and measuring outcomes (function, localization, interactions) .
Common technical challenges and their solutions:
Antibody specificity issues:
Validate antibodies using knockout/knockdown controls
Use multiple antibodies targeting different epitopes
Complement antibody-based methods with tag-based approaches
Expression level variability:
Use inducible expression systems to control levels
Quantify expression in each experiment
Normalize results to expression levels
Functional redundancy masking phenotypes:
Identify and simultaneously target homologous proteins
Use different cell types or stress conditions to reveal phenotypes
Consider compensatory mechanisms in data interpretation
Protein instability:
Conflicting results between systems:
Systematically compare experimental conditions
Consider cell type-specific effects
Evaluate differences in protein levels or post-translational modifications
Addressing these challenges requires careful experimental design with appropriate controls and validation approaches following true experimental research design principles .
Validating research tools for C1orf98 studies:
Antibody validation:
Western blot analysis with overexpression and knockdown/knockout controls
Immunoprecipitation followed by mass spectrometry
Multiple antibodies targeting different epitopes should yield consistent results
Peptide competition assays to confirm specificity
Overexpression constructs:
Sequence verification
Expression level quantification
Assessment of tag interference with function or localization
Comparison of different tags and positions (N- or C-terminal)
siRNA/sgRNA validation:
Quantification of knockdown efficiency at mRNA and protein levels
Use of multiple non-overlapping siRNAs/sgRNAs
Rescue experiments with expression constructs resistant to knockdown
Testing for off-target effects through transcriptome analysis
Recombinant protein quality control:
Rigorous validation ensures that experimental outcomes reflect true biological phenomena rather than artifacts, aligning with principles of true experimental design .
Several emerging approaches are transforming uncharacterized protein research:
Integrative structural biology:
Combining cryo-EM, X-ray crystallography, NMR, and computational modeling
High-throughput protein structure prediction using AI tools like AlphaFold
Structure-based function prediction
Single-cell multi-omics:
Correlating protein levels with transcriptome and metabolome at single-cell resolution
Revealing cell type-specific functions
Identifying context-dependent interactions
Genome-wide interaction mapping:
CRISPR screens for genetic interactions
Protein-protein interaction mapping in native contexts
Dynamic interactome analysis under different conditions
Proximity proteomics advancements:
In situ structural and functional analysis:
Super-resolution microscopy for protein localization
FRET-based interaction and conformation studies
Optogenetic tools for acute functional perturbation
These methodologies, when applied to C1orf98, could rapidly accelerate our understanding of its function and relevance to human biology and disease.
A systematic research program for C1orf98 characterization would include:
Phase 1: Foundational characterization (0-12 months)
Expression profiling across tissues and conditions
Subcellular localization
Interactome mapping
Initial loss-of-function phenotyping
Phase 2: Mechanistic investigations (12-24 months)
Structure determination
Biochemical activity assays
Detailed phenotypic analysis in multiple cell types
PTM identification and functional relevance
Phase 3: Physiological context (24-36 months)
Mouse models (knockout/knockin)
Tissue-specific functions
Disease relevance
Therapeutic potential assessment
This program should adhere to true experimental design principles, with careful control of variables, appropriate randomization, and rigorous statistical analysis .