Biology subjects

Namba, S.

Publications and source records attributed to Namba, S..

9 recordsLinked to original sources

bioRxiv2026

Limit-pushing overexpression reveals constraints on protein abundance

Proteins are often classified as toxic or non-toxic without measuring the abundance reached, leaving constraints on tolerable protein abundance unresolved. We established a limit-pushing approach in Saccharomyces cerevisiae combining strong inducible expression with gTOW-mediated high-copy selection to counteract copy-number compensation while measuring protein abundance and growth. Nearly all of approximately 80 chromosome I proteins severely inhibited growth or reduced viability at sufficiently high abundance. We established IE50, the expression level associated with a 50% reduction in growth rate, to quantify their widely varying overexpression tolerance. IE50 was positively associated with predicted structural order and cytoplasmic localization propensity and negatively associated with sulphur content. Single-cell imaging linked higher tolerance to proteins remaining cytoplasmic without becoming aggregation-positive and revealed abundance-dependent changes in localization and organelle morphology. At extreme abundance, Fun12, Nup60, and Pex22 generated distinct large-scale intracellular states through specific sequence regions. These findings establish overexpression toxicity as a quantitative property linked to protein characteristics and reveal both constraints on tolerable abundance and sequence-dependent capacities for intracellular organization.

systems biology↗

bioRxiv2026

Beyond point estimates: quantifying predictive uncertainty reveals hidden dimensions of biological age acceleration and improves risk interpretation

Biological age estimates are increasingly used to study aging, disease risk, and mortality, yet their predictive uncertainty is rarely quantified. Consequently, conventional age-gap measures can treat deviations as equally informative even when the underlying biological age predictions differ substantially in reliability. We developed a framework for uncertainty-aware biological aging that generates calibrated prediction intervals and individualized probabilities of accelerated or decelerated aging alongside point estimates. We applied this framework to the UK Biobank Pharma Proteomics Project, evaluating three composite and eleven organ-specific biological age clocks. Predictive uncertainty varied substantially both within and across clocks, revealing that apparently extreme age gaps can differ markedly in the strength of evidence supporting accelerated or decelerated aging. In particular, low-accuracy clocks, including many organ-specific clocks, provided little evidence for confidently accelerated or decelerated aging. Beyond biological age gaps, prediction-interval width was independently associated with disease risk and mortality, particularly for composite, brain, and immune clocks, suggesting that predictive uncertainty captures an additional dimension of biological aging that may reflect increased molecular heterogeneity and dysregulation associated with aging and disease. We replicated these findings in Biobank Japan and an independent clinical cohort from Stanford. By incorporating individual-specific predictive uncertainty, our framework provides a more informative characterization of biological aging and enables improved individual-level risk stratification for disease prevention and longitudinal monitoring.

bioinformatics↗

bioRxiv2025

Systematic overexpression reveals a conserved spectrum of harmful and beneficial amino acid homorepeats shaped by evolution

Proteins are composed of combinations of 20 amino acids, yet the principles governing their sequence compatibility within living cells remain poorly understood. Here, we evaluated the "neutrality"--an integrated measure of harmful versus beneficial properties--of amino acid homorepeats (PolyX) in Saccharomyces cerevisiae. Using the genetic tug-of-war (gTOW) method to quantify maximum expression limits, we found that neutrality is highly amino-acid-specific and intrinsically linked to physicochemical properties. Hydrophobic repeats (I, V, W, F, Y) were universally harmful and aggregation-prone, while hydrophilic repeats (E, S, N, Q) not only exhibited high neutrality but also actively suppressed the proteotoxic stress and aggregation of host proteins. These experimental neutrality values show a striking correlation with the occurrence and length of homorepeats across diverse eukaryotic proteomes. Our findings suggest that PolyX neutrality defines the "compatible sequence space" of proteins, where certain sequences like Poly10E act as evolutionary buffers to maintain proteostasis. This study provides a quantitative framework for understanding how physical constraints on protein solubility shape the evolution of proteomes and offers a new metric for rational protein design.

systems biology↗

bioRxiv2025

Rare k-mers reveal centromere haplogroups underlying human diversity and cancer translocations

Centromeres are among the most diverse and dynamically evolving regions of the human genome and are commonly affected in various human cancers. However, organized into highly repetitive -satellite higher-order repeats (HORs), human centromere sequences have long resisted detailed genomic analysis. Although the development of long-read sequencing platforms has enabled the analysis of complete centromere sequences, their application to a large set of samples is still largely limited, preventing our understanding of centromere variation and haplotype structures across large human populations and the structural basis of centromere-involving translocations in cancer. Here we show that rare k-mers present in centromeric regions can serve as effective markers for dissecting the complexity of centromere structure, particularly that of active -satellite HOR arrays (aHOR arrays), across human populations and for understanding centromere-involving abnormalities in cancer. Based on rare k-mer-based clustering, centromere aHOR arrays are clustered into discrete haplogroups (aHOR-HGs) with distinct structural features. These k-mers were also used to develop a framework that enables the inference of haplogroups in a given sample based on short-read whole genome sequencing (WGS) data (ascairn). By applying ascairn to large-scale human population datasets (n > 3,300), we revealed the diversity of aHOR-HGs and their geographic histories across populations. The rare k-mer-based approach was also applied to investigate the structure of 1p/19q co-deletion, a highly recurrent centromere-involving translocation in IDH-mutated oligodendrogliomas. Analyzing short-read WGS data from 142 cases with 1p/19q co-deletion using rare k-mers, we showed that breakpoints of 1p/19q co-deletion were mapped to aHOR arrays in chromosomes 1 (D1Z7) and 19 (D19Z3), which was validated by long-read sequencing of two 1p/19q co-deletion-positive cases. Notably, the translocation preferentially involved haplogroups composed of haplotypes containing larger regions susceptible to rearrangement. These results highlight the role of rare k-mers in dissecting the complexity of centromere sequences and their evolutionary history as well as understanding centromere-involving abnormalities associated with human diseases.

genomics↗

bioRxiv2024

Impact of Maximal Overexpression of a Non-toxic Protein on Yeast Cell Physiology

While it is recognized that excess expression of non-essential proteins burdens cell growth, the physiological state of cells under such stress is largely unknown. This is because it is challenging to distinguish between adverse effects arising from the properties of the expressed excess protein (cytotoxicity) and those caused solely by protein overexpression. In this study, we attempted to identify the model protein with the lowest cytotoxicity in yeast cells by introducing a new neutrality index. We found that a non-fluorescent fluorescent protein (mox-YG) and an inactive glycolytic enzyme (Gpm1- CCmut) showed the lowest cytotoxicity. These proteins can be expressed at levels exceeding 40% of total protein while maintaining yeast growth. The transcriptome of cells expressing mox-YG to the limit indicated that the cells were in a nitrogen source requirement state. Proteome analysis revealed increased mitochondrial protein and decreased ribosome abundance, similar to the inactivated state of the TORC1 pathway. The decrease in ribosome abundance was presumably due to defective nucleolus formation, partially rescued by a mutation in the nuclear exosome. These findings suggest that massive overexpression of excess protein, termed protein burden, causes nitrogen source starvation, a metabolic shift toward more energy-efficient respiration, and a ribosomal biosynthesis defect due to an imbalance between ribosomal protein and rRNA synthesis in the nucleolus.

cell biology↗

bioRxiv2024

Toxicity of the model protein 3xGFP arises from degradation overload, not from aggregate formation

While protein aggregation can cause cytotoxicity, it also forms to mitigate cytotoxicity from misfolded proteins, though the nature of these contrasting aggregates remains unclear. We previously found that overproduction (op) of a three green fluorescent protein linked protein (3xGFP) in yeast cells induces giant aggregates, and is detrimental to growth. Here, we investigated the mechanism of growth inhibition by 3xGFP-op using non-aggregative 3xMOX-op as a control. The 3xGFP aggregates were induced by misfolding, and 3xGFP-op had higher cytotoxicity than 3xMOX-op because it perturbs the ubiquitin-proteasome system. Static aggregates formed by 3xGFP-op dynamically trapped Hsp70, causing the heat shock response. Systematic analysis of mutants deficient in the protein quality control suggested that 3xGFP-op did not cause critical Hsp70 depletion and that the formation of aggregates functioned in the direction of mitigating toxicity. Artificial trapping of essential cell cycle regulators into 3xGFP aggregates caused abnormalities in the cell cycle. In conclusion, the formation of the giant 3xGFP aggregates itself is not cytotoxic, as it does not entrap and deplete essential proteins. Rather, it is productive, inducing the heat shock response while preventing an overload to the degradation system.

cell biology↗

bioRxiv2023

Quantification of the escape from X chromosome inactivation with the million cell-scale human single-cell omics datasets reveals heterogeneity of escape across cell types and tissues

One of the two X chromosomes of females is silenced through X chromosome inactivation (XCI) to compensate for the difference in the dosage between sexes. Among the X-linked genes, several genes escape from XCI, which could contribute to the differential gene expression between the sexes. However, the differences in the escape across cell types and tissues are still poorly characterized because no methods could directly evaluate the escape under a physiological condition at the cell-cluster resolution with versatile technology. Here, we developed a method, single-cell Level inactivated X chromosome mapping (scLinaX), which directly quantifies relative gene expression from the inactivated X chromosome with droplet-based single-cell RNA-sequencing (scRNA-seq) data. The scLinaX and differentially expressed genes analyses with the scRNA-seq datasets of [~]1,000,000 blood cells consistently identified the relatively strong degree of escape in lymphocytes compared to myeloid cells. An extension of scLinaX for multi-modal datasets, scLinaX-multi, suggested a stronger degree of escape in lymphocytes than myeloid cells at the chromatin-accessibility level with a 10X multiome dataset. The scLinaX analysis with the human multiple-organ scRNA-seq datasets also identified the relatively strong degree of escape from XCI in lymphoid tissues and lymphocytes. Finally, effect size comparisons of genome-wide association studies between sexes identified the larger effect sizes of the PRKX gene locus-lymphocyte counts association in females than males. This could suggest evidence of the underlying impact of escape on the genotype-phenotype association in humans. Overall, scLinaX and the quantified catalog of escape identified the heterogeneity of escape across cell types and tissues and would contribute to expanding the current understanding of the XCI, escape, and sex differences in gene regulation.

genomics↗

bioRxiv2021

Short 5'UTR enables optimal translation of plant virus tricistronic RNA via leaky scanning

Regardless of the general model of translation in eukaryotic cells, a number of studies suggested that many of mRNAs encode multiple proteins. Leaky scanning, which supplies ribosomes to downstream open reading frames (ORFs) by read-through of upstream ORFs, is the most major regulatory mechanism to translate polycistronic mRNAs. However, the general regulatory factors controlling leaky scanning and their biological relevance have rarely been elucidated, with exceptions such as the Kozak sequence. Here, we have analyzed the strategy of a plant RNA virus to translate three movement proteins from a single RNA molecule through leaky scanning. The in planta and in vitro results indicate that significantly shorter 5' UTR of the most upstream ORF promotes leaky scanning, potentially finetuning the translation efficiency of the three proteins in a single RNA molecule to optimize viral propagation. Moreover, in plant endogenous mRNAs, we found that shorter UTRs were more frequently observed in uORFs of polycistronic mRNAs. We propose that the promotion of leaky scanning induced by a short 5' UTR (LISH), together with the Kozak sequence, is a conserved gene regulation mechanism not only in viruses but also in eukaryotes.

plant biology↗

bioRxiv2020

Multi-sample Full-length Transcriptome Analysis of 22 Breast Cancer Clinical Specimens with Long-Read Sequencing

Although transcriptome alteration is considered as one of the essential drivers of carcinogenesis, conventional short-read RNAseq technology has limited researchers from directly exploring full-length transcripts, only focusing on individual splice sites. We developed a pipeline for Multi-Sample long-read Transcriptome Assembly, MuSTA, and showed through simulations that it enables construction of transcriptome from the transcripts expressed in target samples and more accurate evaluation of transcript usage. We applied it to 22 breast cancer clinical specimens to successfully acquire cohort-wide full-length transcriptome from long-read RNAseq data. By comparing isoform existence and expression between estrogen receptor positive and triple-negative subtypes, we obtained a comprehensive set of subtype-specific isoforms and differentially used isoforms which consisted of both known and unannotated isoforms. We have also found that exon-intron structure of fusion transcripts tends to depend on their genomic regions, and have found three-piece fusion transcripts that were transcribed from complex structural rearrangements. For example, a three-piece fusion transcript resulted in aberrant expression of an endogenous retroviral gene, ERVFRD-1, which is normally expressed exclusively in placenta and supposed to protect fetus from maternal rejection, and expression of which were increased in several TCGA samples with ERVFRD-1 fusions. Our analyses of real clinical specimens and simulated data provide direct evidence that full-length transcript sequencing in multiple samples can add to our understanding of cancer biology and genomics in general.

genomics↗