Biology subjects

Lim, C. T.

Publications and source records attributed to Lim, C. T..

23 records · Page 2Linked to original sources

bioRxiv2019

Emergence of single cell mechanical behavior and polarity within epithelial monolayers drives collective cell migration

The directed migration of cell collectives is essential in various physiological processes, such as epiboly, intestinal epithelial turnover, and convergent extension during morphogenesis as well as during pathological events like wound healing and cancer metastasis1,2. Collective cell migration leads to the emergence of coordinated movements over multiple cells. Our current understanding emphasizes that these movements are mainly driven by large-scale transmission of signals through adherens junctions3,4. In this study, we show that collective movements of epithelial cells can be triggered by polarity signals at the single cell level through the establishment of coordinated lamellipodial protrusions. We designed a minimalistic model system to generate one-dimensional epithelial trains confined in ring shaped patterns that recapitulate rotational movements observed in vitro in cellular monolayers and in vivo in genitalia or follicular cell rotation5-7. Using our system, we demonstrated that cells follow coordinated rotational movements after the establishment of directed Rac1-dependent polarity over the entire monolayer. Our experimental and numerical approaches show that the maintenance of coordinated migration requires the acquisition of a front-back polarity within each single cell but does not require the maintenance of cell-cell junctions. Taken together, these unexpected findings demonstrate that collective cell dynamics in closed environments as observed in multiple in vitro and in vivo situations5,6,8,9 can arise from single cell behavior through a sustained memory of cell polarity.

biophysics↗

bioRxiv2019

Reticulocyte Infection Leads to Altered Behaviour, Drug Sensitivity and Host Cell Remodelling by Plasmodium falciparum.

Plasmodia are host-specific, both at the organism and cellular levels. During asexual development, Plasmodium spp. infect cells of erythroid lineage, with an overall propensity towards reticulocytes. This applies to even Plasmodium (P.) falciparum, the most common causative agent of human malaria, implications of which remain unexplored. Herein, for the first time, we characterize the developmental stages and features of P. falciparum cultured in vitro in young reticulocytes (CD71+) in comparison to standard normocyte (CD71-) cultures. We demonstrate that there are notable differences in the patterns of invasion, development and sensitivity to potent antimalarials (such as artemisinin and dihydroartemisinin) for parasites residing in CD71+ reticulocytes. Through a transcriptomic approach, we report that P. falciparum parasites are able to sense the host cell environment, and calibrate their metabolic and host cell remodelling pathways through differential gene expression. These results form an exciting avenue on which hitherto unexplored interactions between Plasmodium spp and different stages of host red blood cells could be investigated in the broader contexts of drug resistance, host tropism and zoonosis. Author SummaryParasites causing malaria infect red blood cells for development and proliferation during asexual development. This asexual erythrocytic stage determines higher parasite densities and eventual disease manifestation. Although the most virulent species of Plasmodium infecting humans known as Plasmodium falciparum is able to infect red blood cells of all ages, these parasites show a preference for younger blood cells. Of note, the biochemical and biophysical properties of young and adult red blood cells vary significantly. Herein, we undertook a comparative profiling of invasion process, parasite development and drug response of Plasmoddium falciparum in two host cells: young red blood cells (reticulocytes) and mature red blood cells (normocytes). We demonstrate that P. falciparum infects human reticulocytes with higher affinity and demonstrate differential sensitivity to drugs such as artemisinin while they reside within reticulocytes. Furthermore, we show that P. falciparum is able to detect differences in host environment and adapt to it by changing the expression of genes required for host cell remodelling.

microbiology↗

bioRxiv2018

Mechanical Stretch Kills Transformed Cancer Cells

Transformed cancer cells differ from normal cells in several important features like anchorage independence, Warburg effect and mechanosensing. Consequently, transformed cancer cells develop an anaplastic morphology and respond aberrantly to external mechanical forces. Consistent with altered mechano-responsiveness, here we show that transformed cancer cells from many different tissues have reduced growth and become apoptotic upon cyclic stretch as do normal cells after the transformation. When matrix rigidity sensing is restored in transformed cancer cells, they survive and grow faster on soft surface upon cyclic stretch like normal cells but undergo anoikis without stretch by activation of death associated protein kinase1 (DAPK1). In contrast, stretch-dependent apoptosis (mechanoptosis) of transformed cells is driven by stretch-mediated calcium influx and calcium-dependent calpain 2 protease activation on both collagen and fibronectin matrices. Further, mechanosensitive calcium channel, Piezo1 is needed for mechanoptosis. Thus, cyclic stretching of transformed cells from different tissues activates apoptosis, whereas similar stretching of normal cells stimulates growth.

cell biology↗

bioRxiv2018

Compendiums of Cancer Transcriptome for Machine Learning Applications

BackgroundThere exist massive transcriptome profiles in the form of microarray, enabling reuse. The challenge is that they are processed with diverse platforms and preprocessing tools, requiring considerable time and informatics expertise for cross-dataset or cross-cancer analyses. If there exists a single, integrated data source consisting of thousands of samples, similar to TCGA, data-reuse will be facilitated for discovery, analysis, and validation of biomarker-based clinical strategy.\n\nFindingsWe present 11 merged microarray-acquired datasets (MMDs) of major cancer types, curating 8,386 patient-derived tumor and tumor-free samples from 95 GEO datasets. Highly concordant MMD-derived patterns of genome-wide differential gene expression were observed with matching TCGA cohorts. Using machine learning algorithms, we show that clinical models trained from all MMDs, except breast MMD, can be directly applied to RNA-seq-acquired TCGA data with an average accuracy of 0.96 in classifying cancer. Machine learning optimized MMD further aids to reveal immune landscape of human cancers critically needed in disease management and clinical interventions.\n\nConclusionsTo facilitate large-scale meta-analysis, we generated a newly curated, unified, large-scale MMD across 11 cancer types. Besides TCGA, this single data source may serve as an excellent training or test set to apply, develop, and refine machine learning algorithms that can be tapped to better define genomic landscape of human cancers.

bioinformatics↗

bioRxiv2018

Cross-platform meta-analysis reveals common matrisome variation associated with tumor genotypes and immunophenotypes in human cancers

BackgroundRecent sequencing efforts unveil genomic landscapes of the tumor microenvironment. Yet, little is known about the extent to which matrisome pattern is conserved in progressive tumors across diverse cancer types, and thus its clinical impact remains largely unexplored.\n\nFindingsUsing a newly generated, unified data resource, we conducted cross-platform assessment of a measure of altered extra-cellular matrix (ECM) composition and remodeling associated with tumor progression, termed as the matrisome index (TMI). Parallel analyses with TCGA in over 30,000 patient-derived biopsies revealed that TMI is closely associated with mutational load, tumor histopathology, and predictive of patient outcomes. We found an enrichment of specific tumor-infiltrating immune cell populations, signatures predictive of immunotherapy resistance, and several immune checkpoints in tumors with high TMI, suggesting potential role of ECM interaction with immunophenotyes and tumor immune escape mechanisms. Both epithelial cancer cells and carcinoma-associated fibroblasts are potential cellular contributors of such deregulated matrisome.\n\nConclusionsDespite wide spectrum of genetic heterogeneity and dynamic nature, matrisome abnormalities are integral to disease progression. Our resource of a curated compendium of 8,386 genome-wide profiles, molecular and clinical associations, and matrisome-tumor genotype-immunophenotype relationships identify potentially actionable immune targets that may guide personalized immunotherapy.

genomics↗