Biology subjects

Komura, M.

Publications and source records attributed to Komura, M..

3 recordsLinked to original sources

bioRxiv2024

Automated Xeno-Free Chondrogenic Differentiation from Human Embryonic Stem Cells: Enhancing Efficiency and Ensuring High-Quality Mass Production

IntroductionRepairing damaged cartilage poses significant challenges, particularly in cases of congenital cartilage defects such as microtia or congenital tracheal stenosis, or as a consequence of traumatic injury, as the regenerative potential of cartilage is inherently limited. Stem cell therapy and tissue engineering offer promising approaches to overcome these limitations in cartilage healing. However, the challenge lies in the size of cartilage-containing organs, which necessitates a large quantity of cells to fill the damaged areas. Therefore, pluripotent stem cells that can proliferate indefinitely are highly desirable as a cell source. This study aims to delineate the differentiation conditions for cartilage derived from human embryonic stem cells (ESCs) and to develop an automated cell culture system to facilitate mass production for therapeutic applications. MethodsCartilage cell sheets were derived from human ESCs (SEES2, clinical trial-compatible line) by forming embryoid bodies (EBs) with either conventional manual culture or a benchtop multi-pipetter and an automated medium exchange integrated cell incubator, using xeno-free media. Cell sheets were implanted into the subcutaneous tissue of immunodeficient NOG mice to obtain cartilage tissue. The properties of cartilage tissues were examined by histological staining and quantitative PCR analysis. ResultsWe have optimized an efficient xeno-free system for cartilage production with the conventional culture method and successfully transitioned to an automated system. Differentiated cartilage was histologically uniform with cartilage-specific elasticity and strength. The cartilage tissues were stained by alcian blue, safranin O, and toluidine blue, and quantitative PCR showed an increase in differentiation markers such as ACAN, COL2A1, and Vimentin. Automation significantly enhanced the efficiency of human ESC-derived chondrocyte differentiation. The number of constituent cells within EBs and the seeding density of EBs were identified as key factors influencing chondrogenic differentiation efficiency. By automating the process of chondrogenic differentiation, we achieved scalable production of chondrocytes. ConclusionsBy integrating the differentiation protocol with an automated cell culture system, there is potential to produce cartilage of sufficient size for clinical applications in humans. The resulting cartilage tissue holds promise for clinical use in repairing organs such as the trachea, joints, ears, and nose.

cell biology↗

bioRxiv2018

ALPHLARD: a Bayesian method for analyzing HLA genes from whole genome sequence data

Although human leukocyte antigen (HLA) genotyping based on amplicon, whole exome sequence (WES), and RNA sequence data has been achieved in recent years, accurate genotyping from whole genome sequence (WGS) data remains a challenge due to the low depth. Furthermore, there is no method to identify the sequences of unknown HLA types not registered in HLA databases. We developed a Bayesian model, called ALPHLARD, that collects reads potentially generated from HLA genes and accurately determines a pair of HLA types for each of HLA-A, -B, -C, -DPA1, -DPB1, -DQA1, -DQB1, and -DRB1 genes at 6-digit resolution. Furthermore, ALPHLARD can detect rare germline variants not stored in HLA databases and call somatic mutations from paired normal and tumor sequence data. We illustrate the capability of ALPHLARD using 253 WES data and 25 WGS data from Illumina platforms. By comparing the results of HLA genotyping from SBT and amplicon sequencing methods, ALPHLARD achieved 98.8% for WES data and 98.5% for WGS data at 4-digit resolution. We also detected three somatic point mutations and one case of loss of heterozygosity in the HLA genes from the WGS data. ALPHLARD showed good performance for HLA genotyping even from low-coverage data. It also has a potential to detect rare germline variants and somatic mutations in HLA genes. It would help to fill in the current gaps in HLA reference databases and unveil the immunological significance of somatic mutations identified in HLA genes.

bioinformatics↗

bioRxiv2018

Immuno-genomic PanCancer Landscape Reveals Diverse Immune Escape Mechanisms and Immuno-Editing Histories

Immune reactions in the tumor micro-environment are one of the cancer hallmarks and emerging immune therapies have been proven effective in many types of cancer. To investigate cancer genome-immune interactions and the role of immuno-editing or immune escape mechanisms in cancer development, we analyzed 2,834 whole genomes and RNA-seq datasets across 31 distinct tumor types from the PanCancer Analysis of Whole Genomes (PCAWG) project with respect to key immuno-genomic aspects. We show that selective copy number changes in immune-related genes could contribute to immune escape. Furthermore, we developed an index of the immuno-editing history of each tumor sample based on the information of mutations in exonic regions and pseudogenes. Our immuno-genomic analyses of pan-cancer analyses have the potential to identify a subset of tumors with immunogenicity and diverse background or intrinsic pathways associated with their immune status and immuno-editing history.

genomics↗