MYL5 Human

What is MYL5 and what cellular functions has it been associated with?

MYL5 is a 173 amino acid protein classified as a myosin regulatory light chain (RLC) of the MLC2 type. While it remained poorly characterized until recently, experimental evidence shows it plays critical roles in mitotic spindle formation and cell division. MYL5 shows dynamic subcellular localization, redistributing from the nucleus and cytoplasm during interphase to the spindle poles throughout mitosis . Functionally, it's involved in ensuring proper chromosome segregation, as depletion studies demonstrate its requirement for maintaining spindle integrity and preventing mitotic defects such as multipolar spindles and lagging chromosomes . Beyond cell division, MYL5 has also been implicated in transcriptional regulation, as myosin light chains can associate with chromatin to modulate gene expression .

What are the structural characteristics of human MYL5 protein?

Human MYL5 contains three EF hand domains, which are helix-loop-helix structural motifs predicted to be important for calcium binding, a characteristic shared with other myosin regulatory light chains . The protein exists in two confirmed isoforms: a 19.5 kD isoform (UniProtKB-Q02045-1) and a shorter 14.9 kD isoform (UniProtKB-Q02045-2) . Phylogenetic analysis indicates that MYL5 is well-conserved among vertebrates, suggesting evolutionary importance of its function . When designing experiments to study MYL5, researchers should consider these structural elements, particularly when creating fusion proteins or detecting the protein via antibodies that might recognize specific domains.

How can researchers effectively detect and quantify MYL5 expression?

To detect and quantify MYL5 expression, researchers should employ a multi-method approach. For protein-level detection, Western blotting using validated anti-MYL5 antibodies capable of distinguishing between the two isoforms (19.5kD and 14.9kD) is recommended . For mRNA quantification, RT-qPCR primers should be designed to capture potential splice variants. For localization studies, immunofluorescence microscopy using specific antibodies has successfully revealed MYL5's dynamic localization pattern throughout the cell cycle .

For larger-scale analyses, researchers can leverage public databases and tools such as TIMER2.0, GEPIA2, and LinkedOmics, which have been successfully used to analyze MYL5 expression across multiple cancer types and correlate it with clinical parameters . When studying cellular localization, researchers should consider cell synchronization techniques to capture cell cycle-specific localization patterns, as MYL5 shows dynamic redistribution from interphase to mitosis .

How is MYL5 expression regulated during the cell cycle?

MYL5 protein levels remain relatively constant throughout most of the cell cycle, showing steady expression in G1/S and G2/M phases, with a slight decrease during mitotic exit . This pattern was discovered through cell synchronization experiments using thymidine treatment to arrest cells at G1/S, followed by release and time-course protein extraction . Cyclin B levels, which decrease during mitotic exit, can serve as a useful control when monitoring cell cycle progression in MYL5 studies .

Despite relatively stable protein levels, MYL5 undergoes significant changes in subcellular localization, redistributing from the nucleus and cytoplasm in interphase to concentrate at spindle poles during mitosis . This indicates that post-translational modifications or protein-protein interactions, rather than transcriptional regulation, may be the primary mechanisms controlling MYL5 function throughout the cell cycle.

What are the key protein interactions of MYL5?

MYL5 has been shown to directly interact with MYO10 (Myosin X), with this interaction occurring specifically at the spindle poles during mitosis . The interaction between MYL5 and MYO10 has been verified through co-immunoprecipitation experiments, and the IQ motifs of MYO10 appear to be crucial for this interaction . When MYO10 lacks these IQ motifs (MYO10-IQL), the binding to MYL5 is significantly reduced .

To study this interaction, researchers have successfully used in vitro binding experiments with tagged proteins (HA-Myl5 and FLAG-MYO10) followed by co-immunoprecipitation and immunoblotting . For in vivo studies, co-localization can be visualized by immunofluorescence microscopy using specific antibodies against both proteins, or by using fluorescently tagged proteins such as GFP-Myl5 . When designing interaction studies, researchers should consider both full-length proteins and truncated versions to identify specific binding domains.

What methodological approaches can researchers use to study MYL5's role in mitotic spindle formation?

To investigate MYL5's role in mitotic spindle formation, researchers should employ a combination of loss-of-function and imaging techniques. RNA interference (RNAi) using validated siRNA oligonucleotides has been effectively used to deplete MYL5 in cells . For optimal depletion, researchers should test multiple siRNAs (e.g., siM1-siM4) and confirm knockdown efficiency via immunoblotting . Alternative approaches include CRISPR-Cas9 gene editing for complete knockout or the use of dominant-negative mutants.

For phenotypic analysis, fixed-cell immunofluorescence microscopy with anti-α-Tubulin antibodies allows visualization of spindle defects . Live-cell imaging using fluorescently tagged tubulin can capture dynamic abnormalities. When quantifying mitotic defects, researchers should categorize abnormalities (e.g., multipolar spindles, lagging chromosomes) and perform statistical analysis comparing control and MYL5-depleted cells . For example, depletion of MYL5 in HeLa cells led to a significant increase in prometaphase cells with multipolar spindles (20.75±3.59% compared to 7.5±1.29% in control cells, p=0.0004) and anaphase cells with lagging chromosomes (32.25±2.5% versus control) .

How can the prognostic value of MYL5 in cancer be systematically evaluated?

Correlation with clinicopathological features requires access to patient metadata, which is available through The Cancer Genome Atlas (TCGA) and can be analyzed using tools like TIMER2.0 . For breast cancer specifically, MYL5 expression levels have shown significant correlations with clinical parameters as demonstrated in this data excerpt:

Validation studies should include immunohistochemistry on tissue microarrays with adequate sample sizes and proper controls, followed by multivariate Cox regression analysis to determine independent prognostic value .

What techniques are most effective for investigating the relationship between MYL5 and immune infiltration?

To investigate the relationship between MYL5 and immune infiltration, researchers should utilize computational deconvolution methods combined with experimental validation. Several computational algorithms have been successfully applied, including EPIC, MCPCOUNTER, XCELL, and TIDE, which estimate immune cell composition from bulk RNA-seq data . The TIMER2 web server specifically allows analysis of correlations between MYL5 expression and cancer-associated fibroblasts across TCGA tumors .

For more detailed analysis, researchers can examine correlations between MYL5 expression and specific immune cell gene markers using tools like GEPIA2 and TIMER2.0 . The TISIDB database provides additional information on associations between MYL5 and lymphocytes, immune modulators (immunosuppressants and immunostimulants), and chemokines .

Experimental validation should include multiplex immunofluorescence or immunohistochemistry on tissue sections to visualize MYL5-expressing cells and immune infiltrates simultaneously. Flow cytometry analysis of dissociated tumors can quantify immune populations in relation to MYL5 expression levels. Single-cell RNA-seq offers the highest resolution for examining MYL5 expression in specific cell types within the tumor microenvironment.

How should researchers address the context-dependent expression of MYL5 across different cancer types?

The context-dependent expression of MYL5 across different cancer types presents a research challenge, as MYL5 is upregulated in cervical cancer but downregulated in breast and brain cancers . To address this complexity, researchers should:

• First establish expression profiles across multiple cancer types using pan-cancer databases such as TCGA through tools like GEPIA2 and TIMER2.0 .

• Perform tissue-specific analyses to identify factors that might influence MYL5 expression in different contexts, such as tissue-specific transcription factors, epigenetic regulators, or microRNAs.

• Conduct pathway analysis using tools like LinkedOmics to identify differentially expressed genes correlated with MYL5 across cancer types . Gene Set Enrichment Analysis (GSEA) can reveal biological processes, molecular functions, cellular components, and signaling pathways associated with MYL5 in each cancer context .

• Design comparative in vitro experiments using cell lines from multiple cancer types with variable MYL5 expression. Manipulate MYL5 levels through overexpression or knockdown and compare phenotypic consequences.

• Consider microenvironmental factors such as hypoxia, which may influence MYL5 expression through its interaction with HIF-1α .

This multi-faceted approach can help elucidate why MYL5 functions as an oncogene in some contexts and a tumor suppressor in others.

What experimental design is optimal for investigating the bidirectional regulation between MYL5 and HIF-1α?

To investigate the bidirectional regulation between MYL5 and HIF-1α, researchers should implement a comprehensive experimental design that addresses both directions of regulation.

For studying HIF-1α regulation of MYL5:

• Create cellular hypoxic conditions using hypoxia chambers (1-2% O2) or chemical mimetics (CoCl2, DMOG).

• Monitor MYL5 mRNA and protein levels after hypoxia induction.

• Perform chromatin immunoprecipitation (ChIP) to identify potential HIF-1α binding sites in the MYL5 promoter region.

• Use reporter assays with the MYL5 promoter to confirm direct transcriptional regulation.

• Validate findings using HIF-1α knockdown or knockout cells.

For studying MYL5 regulation of HIF-1α:

• Generate MYL5 overexpression and knockdown cell models.

• Assess HIF-1α protein stability through pulse-chase experiments and ubiquitination assays.

• Examine HIF-1α nuclear localization via cellular fractionation and immunofluorescence.

• Measure HIF-1α transcriptional activity using reporter assays with hypoxia response elements.

• Analyze expression of established HIF-1α target genes after MYL5 manipulation.

In both directions, researchers should consider post-translational modifications and protein-protein interactions. Co-immunoprecipitation followed by mass spectrometry can identify potential interacting partners in the MYL5-HIF-1α regulatory axis . Finally, functional assays measuring angiogenesis, metabolism, and cell migration will connect this bidirectional regulation to cancer-relevant phenotypes.

What bioinformatic tools and statistical methods are most valuable for MYL5 research in cancer studies?

Cancer researchers studying MYL5 should utilize a suite of bioinformatic tools and statistical methods to generate comprehensive insights. Based on successful approaches documented in the literature, the following tools have proven particularly valuable:

• Expression analysis: TIMER2.0 and GEPIA2 for comparing MYL5 expression between tumor and normal tissues across multiple cancer types .

• Survival analysis: Kaplan-Meier plotter and PrognoScan for correlating MYL5 expression with patient outcomes . Statistical significance should be evaluated using log-rank tests and hazard ratios with 95% confidence intervals.

• Clinical correlation: Chi-squared tests and Fisher's exact tests for categorical variables, and Spearman's/Pearson's correlation analyses for continuous variables .

• Immune infiltration analysis: EPIC, MCPCOUNTER, XCELL, and TIDE algorithms for estimating immune cell compositions . Correlations should be assessed using purity-adjusted Spearman's rank correlation tests.

• Pathway analysis: LinkedOmics for identifying genes correlated with MYL5 and performing Gene Set Enrichment Analysis (GSEA) .

• Visualization: Volcano plots and heat maps for displaying differential expression data, and scatter plots for correlation analyses .

For statistical robustness, researchers should incorporate multiple testing corrections (e.g., Benjamini-Hochberg procedure) when performing genome-wide analyses and set significance thresholds at p < 0.05 unless otherwise specified .

How can researchers differentiate between the functions of the two MYL5 isoforms?

To differentiate between the functions of the two MYL5 isoforms (19.5 kD and 14.9 kD), researchers should employ isoform-specific approaches:

• Create isoform-specific expression constructs for both the 19.5 kD (UniProtKB-Q02045-1) and 14.9 kD (UniProtKB-Q02045-2) isoforms .

• Design isoform-specific siRNAs or CRISPR guides targeting unique regions of each variant.

• Generate isoform-specific antibodies that can distinguish between the two proteins on Western blots and in immunofluorescence studies .

• For rescue experiments, deplete endogenous MYL5 using siRNAs targeting common regions, then reintroduce either isoform individually to assess functional recovery.

• Perform domain mapping studies to identify functional differences based on the structural distinctions between isoforms.

• Use live-cell imaging with fluorescently tagged isoforms to track potential differences in localization dynamics throughout the cell cycle.

• Conduct protein-protein interaction studies (co-IP, proximity labeling) for each isoform to identify isoform-specific binding partners.

• Analyze isoform expression ratios across different tissues and cancer types to identify contexts where one isoform might predominate.

This comprehensive approach will help delineate the potentially distinct roles of these two protein variants in cell division and cancer progression.