Linking antigen specific T-cell dynamics in a microfluidic chip to single cell transcription patterns.

A new non-invasive screening profile has been realized that can aid in determining T-cell activation state at single-cell level. Production of activated T-cells with good specificity and stable proliferation is greatly beneficial for advancing adoptive immunotherapy as innate immunological cells are not effective in recognizing and eliminating cancer as expected. The screening method is realized by relating intracellular Ca2+ intensity and motility of T-cells interacting with APC (Antigen Presenting Cells) in a microfluidic chip. The system is tested using APC pulsed with OVA257-264 peptide and its modified affinities (N4, Q4, T4 and V4), and the T-cells from OT-1 mice. In addition, single cell RNA sequencing reveals the activation states of the cells and the clusters from the derived profiles can be indicative of the T-cell activation state. The presented system here can be versatile for a comprehensive application to proceed with T-cell-based immunotherapy and screen the antigen-specific T-cells with excellent efficiency and high proliferation.

A highly sensitive and accurate gene expression analysis by sequencing ("bead-seq") for a single cell.

Analyses of gene expressions in single cells are important for understanding detailed biological phenomena. Here, a highly sensitive and accurate method by sequencing (called "bead-seq") to obtain a whole gene expression profile for a single cell is proposed. A key feature of the method is to use a complementary DNA (cDNA) library on magnetic beads, which enables adding washing steps to remove residual reagents in a sample preparation process. By adding the washing steps, the next steps can be carried out under the optimal conditions without losing cDNAs. Error sources were carefully evaluated to conclude that the first several steps were the key steps. It is demonstrated that bead-seq is superior to the conventional methods for single-cell gene expression analyses in terms of reproducibility, quantitative accuracy, and biases caused during sample preparation and sequencing processes.

A single amplified genome catalog reveals the dynamics of mobilome and resistome in the human microbiome.

BACKGROUND: The increase in metagenome-assembled genomes (MAGs) has advanced our understanding of the functional characterization and taxonomic assignment within the human microbiome. However, MAGs, as population consensus genomes, often aggregate heterogeneity among species and strains, thereby obfuscating the precise relationships between microbial hosts and mobile genetic elements (MGEs). In contrast, single amplified genomes (SAGs) derived via single-cell genome sequencing can capture individual genomic content, including MGEs. RESULTS: We introduce the first substantial SAG dataset (bbsag20) from the human oral and gut microbiome, comprising 17,202 SAGs above medium-quality without co-assembly. This collection unveils a diversity of bacterial lineages across 312 oral and 647 gut species, demonstrating different taxonomic compositions from MAGs. Moreover, the SAGs showed cellular-level evidence of the translocation of oral bacteria to the gut. We also identified broad-host-range MGEs harboring antibiotic resistance genes (ARGs), which were not detected in the MAGs. CONCLUSIONS: The difference in taxonomic composition between SAGs and MAGs indicates that combining both methods would be effective in expanding the genome catalog. By connecting mobilomes and resistomes in individual samples, SAGs could meticulously chart a dynamic network of ARGs on MGEs, pinpointing potential ARG reservoirs and their spreading patterns in the microbial community. Video Abstract.

Uncultured prokaryotic genomes in the spotlight: An examination of publicly available data from metagenomics and single-cell genomics.

Owing to the ineffectiveness of traditional culture techniques for the vast majority of microbial species, culture-independent analyses utilizing next-generation sequencing and bioinformatics have become essential for gaining insight into microbial ecology and function. This mini-review focuses on two essential methods for obtaining genetic information from uncultured prokaryotes, metagenomics and single-cell genomics. We analyzed the registration status of uncultured prokaryotic genome data from major public databases and assessed the advantages and limitations of both the methods. Metagenomics generates a significant quantity of sequence data and multiple prokaryotic genomes using straightforward experimental procedures. However, in ecosystems with high microbial diversity, such as soil, most genes are presented as brief, disconnected contigs, and lack association of highly conserved genes and mobile genetic elements with individual species genomes. Although technically more challenging, single-cell genomics offers valuable insights into complex ecosystems by providing strain-resolved genomes, addressing issues in metagenomics. Recent technological advancements, such as long-read sequencing, machine learning algorithms, and in silico protein structure prediction, in combination with vast genomic data, have the potential to overcome the current technical challenges and facilitate a deeper understanding of uncultured microbial ecosystems and microbial dark matter genes and proteins. In light of this, it is imperative that continued innovation in both methods and technologies take place to create high-quality reference genome databases that will support future microbial research and industrial applications.

Revealing within-species diversity in uncultured human gut bacteria with single-cell long-read sequencing.

Obtaining complete and accurate bacterial genomes is vital for studying the characteristics of uncultured bacteria. Single-cell genomics is a promising approach for the culture-independent recovery of bacterial genomes from individual cells. However, single-amplified genomes (SAGs) often have fragmented and incomplete sequences due to chimeric and biased sequences introduced during the genome amplification process. To address this, we developed a single-cell amplified genome long-read assembly (scALA) workflow to construct complete circular SAGs (cSAGs) from long-read single-cell sequencing data of uncultured bacteria. We used the SAG-gel platform, which is both cost-effective and high-throughput, to obtain hundreds of short-read and long-read sequencing data for specific bacterial strains. The scALA workflow generated cSAGs by repeated in silico processing for sequence bias reduction and contig assembly. From 12 human fecal samples, including two cohabitant groups, scALA generated 16 cSAGs of three specifically targeted bacterial species: Anaerostipes hadrus, Agathobacter rectalis, and Ruminococcus gnavus. We discovered strain-specific structural variations shared among cohabiting hosts, while all cSAGs of the same species showed high homology in aligned genomic regions. A. hadrus cSAGs exhibited 10 kbp-long phage insertions, various saccharide metabolic capabilities, and different CRISPR-Cas systems in each strain. The sequence similarity of A. hadrus genomes did not necessarily correspond with orthologous functional genes, while host geographical regionality seemed to be highly related to gene possession. scALA allowed us to obtain closed circular genomes of specifically targeted bacteria from human microbiota samples, leading to an understanding of within-species diversities, including structural variations and linking mobile genetic elements, such as phages, to hosts. These analyses provide insight into microbial evolution, the adaptation of the community to environmental changes, and interactions with hosts. cSAGs constructed using this method can expand bacterial genome databases and our understanding of within-species diversities in uncultured bacteria.

Target enrichment of uncultured human oral bacteria with phage-derived molecules found by single-cell genomics.

Advances in culture-independent microbial analysis, such as metagenomics and single-cell genomics, have significantly increased our understanding of microbial lineages. While these methods have uncovered a large number of novel microbial taxa, many remain uncultured, and their function and mode of existence in the environment are still unknown. This study aims to explore the use of bacteriophage-derived molecules as probes for detecting and isolating uncultured bacteria. Here, we proposed multiplex single-cell sequencing to obtain massive uncultured oral bacterial genomes and searched prophage sequences from over 450 obtained human oral bacterial single-amplified genomes (SAGs). The focus was on the cell wall binding domain (CBD) in phage endolysin, and fluorescent protein-fused CBDs were generated based on several CBD gene sequences predicted from Streptococcus SAGs. The ability of the Streptococcus prophage-derived CBDs to detect and enrich specific Streptococcus species from human saliva while maintaining cell viability was confirmed by magnetic separation and flow cytometry. The approach to phage-derived molecule generation based on uncultured bacterial SAG is expected to improve the process of designing molecules that selectively capture or detect specific bacteria, notably from uncultured gram-positive bacteria, and will have applications in isolation and in situ detection of beneficial or pathogenic bacteria.

Identification of two cancer stem cell-like populations in triple-negative breast cancer xenografts.

Gene expression analysis at the single-cell level by next-generation sequencing has revealed the existence of clonal dissemination and microheterogeneity in cancer metastasis. The current spatial analysis technologies can elucidate the heterogeneity of cell-cell interactions in situ. To reveal the regional and expressional heterogeneity in primary tumors and metastases, we performed transcriptomic analysis of microtissues dissected from a triple-negative breast cancer (TNBC) cell line MDA-MB-231 xenograft model with our automated tissue microdissection punching technology. This multiple-microtissue transcriptome analysis revealed three cancer cell-type clusters in the primary tumor and axillary lymph node metastasis, two of which were cancer stem cell (CSC)-like clusters (CD44/MYC-high, HMGA1-high). Reanalysis of public single-cell RNA-sequencing datasets confirmed that the two CSC-like populations existed in TNBC xenograft models and in TNBC patients. The diversity of these multiple CSC-like populations could cause differential anticancer drug resistance, increasing the difficulty of curing this cancer.

Exploring strain diversity of dominant human skin bacterial species using single-cell genome sequencing.

To understand the role of the skin commensal bacterial community in skin health and the spread of pathogens, it is crucial to identify genetic differences in the bacterial strains corresponding to human individuals. A culture-independent genomics approach is an effective tool for obtaining massive high-quality bacterial genomes. Here we present a single-cell genome sequencing to obtain comprehensive whole-genome sequences of uncultured skin bacteria from skin swabs. We recovered 281 high-quality (HQ) and 244 medium-quality single-amplified genomes (SAGs) of multiple skin bacterial species from eight individuals, including cohabiting group. Single-cell sequencing outperformed in the genome recovery from the same skin swabs, showing 10-fold non-redundant strain genomes compared to the shotgun metagenomic sequencing and binning approach. We then focused on the abundant skin bacteria and identified intra-species diversity, especially in 47 Moraxella osloensis derived HQ SAGs, characterizing the strain-level heterogeneity at mobile genetic element profiles, including plasmids and prophages. Even between the cohabiting individual hosts, they have unique skin bacterial strains in the same species, which shows microdiversity in each host. Genetic and functional differences between skin bacterial strains are predictive of in vivo competition to adapt bacterial genome to utilize the sparse nutrients available on the skin or produce molecules that inhibit the colonization of other microbes or alter their behavior. Thus, single-cell sequencing provides a large number of genomes of higher resolution and quality than conventional metagenomic analysis and helps explore the skin commensal bacteria at the strain level, linking taxonomic and functional information.

Strain-level profiling of viable microbial community by selective single-cell genome sequencing.

Culture-independent analysis with high-throughput sequencing has been widely used to characterize bacterial communities. However, signals derived from non-viable bacteria and non-cell DNA may inhibit its characterization. Here, we present a method for viable bacteria-targeted single-cell genome sequencing, called PMA-SAG-gel, to obtain comprehensive whole-genome sequences of surviving uncultured bacteria from microbial communities. PMA-SAG-gel uses gel matrixes that enable sequential enzymatic reactions for cell lysis and genome amplification of viable single cells from the microbial communities. PMA-SAG-gel removed the single-amplified genomes (SAGs) derived from dead bacteria and enabled selective sequencing of viable bacteria in the model samples of Escherichia coli and Bacillus subtilis. Next, we demonstrated the recovery of near-complete SAGs of eight oxygen-tolerant bacteria, including Bacteroides spp. and Phocaeicola spp., from 1331 human feces SAGs. We found the presence of two different strains in each species and identified their specific genes to investigate the metabolic functions. The survival profile of an entire population at the strain level will provide the information for understanding the characteristics of the surviving bacteria under the specific environments or sample processing and insights for quality assessment of live bacterial products or fecal microbiota transplantation and for understanding the effect of antimicrobial treatments.

Integrated spatial analysis of gene mutation and gene expression for understanding tumor diversity in formalin-fixed paraffin-embedded lung adenocarcinoma.

Introduction: A deeper understanding of intratumoral heterogeneity is essential for prognosis prediction or accurate treatment plan decisions in clinical practice. However, due to the cross-links and degradation of biomolecules within formalin-fixed paraffin-embedded (FFPE) specimens, it is challenging to analyze them. In this study, we aimed to optimize the simultaneous extraction of mRNA and DNA from microdissected FFPE tissues (φ = 100 µm) and apply the method to analyze tumor diversity in lung adenocarcinoma before and after erlotinib administration. Method: Two magnetic beads were used for the simultaneous extraction of mRNA and DNA. The decross-linking conditions were evaluated for gene mutation and gene expression analyses of microdissected FFPE tissues. Lung lymph nodes before treatment and lung adenocarcinoma after erlotinib administration were collected from the same patient and were preserved as FFPE specimens for 4 years. Gene expression and gene mutations between histologically classified regions of lung adenocarcinoma (pre-treatment tumor in lung lymph node biopsies and post-treatment tumor, normal lung, tumor stroma, and remission stroma, in resected lung tissue) were compared in a microdissection-based approach. Results: Using the optimized simultaneous extraction of DNA and mRNA and whole-genome amplification, we detected approximately 4,000-10,000 expressed genes and the epidermal growth factor receptor (EGFR) driver gene mutations from microdissected FFPE tissues. We found the differences in the highly expressed cancer-associated genes and the positive rate of EGFR exon 19 deletions among the tumor before and after treatment and tumor stroma, even though they were collected from tumors of the same patient or close regions of the same specimen. Conclusion: Our integrated spatial analysis method would be applied to various FFPE pathology specimens providing area-specific gene expression and gene mutation information.

Reproducible and sensitive micro-tissue RNA sequencing from formalin-fixed paraffin-embedded tissues for spatial gene expression analysis.

Spatial transcriptome analysis of formalin-fixed paraffin-embedded (FFPE) tissues using RNA-sequencing (RNA-seq) provides interactive information on morphology and gene expression, which is useful for clinical applications. However, despite the advantages of long-term storage at room temperature, FFPE tissues may be severely damaged by methylene crosslinking and provide less gene information than fresh-frozen tissues. In this study, we proposed a sensitive FFPE micro-tissue RNA-seq method that combines the punching of tissue sections (diameter: 100 µm) and the direct construction of RNA-seq libraries. We evaluated a method using mouse liver tissues at two years after fixation and embedding and detected approximately 7000 genes in micro-punched tissue-spots (thickness: 10 µm), similar to that detected with purified total RNA (2.5 ng) equivalent to the several dozen cells in the spot. We applied this method to clinical FFPE specimens of lung cancer that had been fixed and embedded 6 years prior, and found that it was possible to determine characteristic gene expression in the microenvironment containing tumor and non-tumor cells of different morphologies. This result indicates that spatial gene expression analysis of the tumor microenvironment is feasible using FFPE tissue sections stored for extensive periods in medical facilities.

Recovery of strain-resolved genomes from human microbiome through an integration framework of single-cell genomics and metagenomics.

BACKGROUND: Obtaining high-quality (HQ) reference genomes from microbial communities is crucial for understanding the phylogeny and function of uncultured microbes in complex microbial ecosystems. Despite improvements in bioinformatic approaches to generate curated metagenome-assembled genomes (MAGs), existing metagenome binners obtain population consensus genomes but they are nowhere comparable to genomes sequenced from isolates in terms of strain level resolution. Here, we present a framework for the integration of single-cell genomics and metagenomics, referred to as single-cell (sc) metagenomics, to reconstruct strain-resolved genomes from microbial communities at once. RESULTS: Our sc-metagenomics integration framework, termed SMAGLinker, uses single-cell amplified genomes (SAGs) generated using microfluidic technology as binning guides and integrates them with metagenome-assembled genomes (MAGs) to recover improved draft genomes. We compared sc-metagenomics with the metagenomics-alone approach using conventional metagenome binners. The sc-metagenomics approach showed precise contig binning and higher recovery rates (>97%) of rRNA and plasmids than conventional metagenomics in genome reconstruction from the cell mock community. In human microbiota samples, sc-metagenomics recovered the largest number of genomes with a total of 103 gut microbial genomes (21 HQ, with 65 showing >90% completeness) and 45 skin microbial genomes (10 HQ, with 40 showing >90% completeness), respectively. Conventional metagenomics recovered one Staphylococcus hominis genome, whereas sc-metagenomics recovered two S. hominis genomes from identical skin microbiota sample. Single-cell sequencing revealed that these S. hominis genomes were derived from two distinct strains harboring specifically different plasmids. We found that all conventional S. hominis MAGs had a substantial lack or excess of genome sequences and contamination from other Staphylococcus species (S. epidermidis). CONCLUSIONS: SMAGLinker enabled us to obtain strain-resolved genomes in the mock community and human microbiota samples by assigning metagenomic sequences correctly and covering both highly conserved genes such as rRNA genes and unique extrachromosomal elements, including plasmids. SMAGLinker will provide HQ genomes that are difficult to obtain using metagenomics alone and will facilitate the understanding of microbial ecosystems by elucidating detailed metabolic pathways and horizontal gene transfer networks. SMAGLinker is available at https://github.com/kojiari/smaglinker . Video abstract.

Cortical transcriptome analysis after spinal cord injury reveals the regenerative mechanism of central nervous system in CRMP2 knock-in mice.

Recent studies have shown that mutation at Ser522 causes inhibition of collapsin response mediator protein 2 (CRMP2) phosphorylation and induces axon elongation and partial recovery of the lost sensorimotor function after spinal cord injury (SCI). We aimed to reveal the intracellular mechanism in axotomized neurons in the CRMP2 knock-in (CRMP2KI) mouse model by performing transcriptome analysis in mouse sensorimotor cortex using micro-dissection punching system. Prior to that, we analyzed the structural pathophysiology in axotomized or neighboring neurons after SCI and found that somatic atrophy and dendritic spine reduction in sensorimotor cortex were suppressed in CRMP2KI mice. Further analysis of the transcriptome has aided in the identification of four hemoglobin genes Hba-a1, Hba-a2, Hbb-bs, and Hbb-bt that are significantly upregulated in wild-type mice with concomitant upregulation of genes involved in the oxidative phosphorylation and ribosomal pathways after SCI. However, we observed substantial upregulation in channel activity genes and downregulation of genes regulating vesicles, synaptic function, glial cell differentiation in CRMP2KI mice. Moreover, the transcriptome profile of CRMP2KI mice has been discussed wherein energy metabolism and neuronal pathways were found to be differentially regulated. Our results showed that CRMP2KI mice displayed improved SCI pathophysiology not only via microtubule stabilization in neurons, but also possibly via the whole metabolic system in the central nervous system, response changes in glial cells, and synapses. Taken together, we reveal new insights on SCI pathophysiology and the regenerative mechanism of central nervous system by the inhibition of CRMP2 phosphorylation at Ser522. All these experiments were performed in accordance with the guidelines of the Institutional Animal Care and Use Committee at Waseda University, Japan (2017-A027 approved on March 21, 2017; 2018-A003 approved on March 25, 2018; 2019-A026 approved on March 25, 2019).

Distinctive Regulation of Emotional Behaviors and Fear-Related Gene Expression Responses in Two Extended Amygdala Subnuclei With Similar Molecular Profiles.

The central nucleus of the amygdala (CeA) and the lateral division of the bed nucleus of the stria terminalis (BNST) are the two major nuclei of the central extended amygdala that plays essential roles in threat processing, responsible for emotional states such as fear and anxiety. While some studies suggested functional differences between these nuclei, others showed anatomical and neurochemical similarities. Despite their complex subnuclear organization, subnuclei-specific functional impact on behavior and their underlying molecular profiles remain obscure. We here constitutively inhibited neurotransmission of protein kinase C-δ-positive (PKCδ+) neurons-a major cell type of the lateral subdivision of the CeA (CeL) and the oval nucleus of the BNST (BNSTov)-and found striking subnuclei-specific effects on fear- and anxiety-related behaviors, respectively. To obtain molecular clues for this dissociation, we conducted RNA sequencing in subnuclei-targeted micropunch samples. The CeL and the BNSTov displayed similar gene expression profiles at the basal level; however, both displayed differential gene expression when animals were exposed to fear-related stimuli, with a more robust expression change in the CeL. These findings provide novel insights into the molecular makeup and differential engagement of distinct subnuclei of the extended amygdala, critical for regulation of threat processing.

High-Quality Draft Single-Cell Genome Sequences of Two Gammaproteobacteria Strains Sampled from Soil in a Strawberry Farm.

Here, we present high-quality draft single-cell genome sequences of Gammaproteobacteria strains BBSC-SA01 and BBSC-SA02, obtained from uncultivated cells of soil in a strawberry farm using the single-cell sequencing platform bit-MAP. These draft genomes putatively represent novel species within Gammaproteobacteria and allow further investigation into the soil microbiome.

Time-lapse single-cell transcriptomics reveals modulation of histone H3 for dormancy breaking in fission yeast.

How quiescent cells break dormancy is a key issue in eukaryotic cells including cancer. Fungal spores, for example, remain quiescent for long periods until nourished, although the mechanisms by which dormancy is broken remain enigmatic. Transcriptome analysis could provide a clue, but methods to synchronously germinate large numbers of spores are lacking, and thus it remains a challenge to analyse gene expression upon germination. Hence, we develop methods to assemble transcriptomes from individual, asynchronous spore cells of fission yeast undergoing germination to assess transcriptomic changes over time. The virtual time-lapse analyses highlights one of three copies of histone H3 genes whose transcription fluctuates during the initial stage of germination. Disruption of this temporal fluctuation causes defects in spore germination despite no visible defects in other stages of the life cycle. We conclude that modulation of histone H3 expression is a crucial 'wake-up' trigger at dormancy breaking.

Evaluation of the effects of cell-dispensing using an inkjet-based bioprinter on cell integrity by RNA-seq analysis.

Bioprinting technology is expected to be applied in the fields of regenerative medicine and drug discovery. There are several types of bioprinters, especially inkjet-based bioprinter, which can be used not only as a printer for arranging cells but also as a precision cell-dispensing device with controlled cell numbers similar to a fluorescence activated cell sorter (FACS). Precise cell dispensers are expected to be useful in the fields of drug discovery and single-cell analysis. However, there are enduring concerns about the impacts of cell dispensers on cell integrity, particularly on sensitive cells, such as stem cells. In response to the concerns stated above, we developed a stress-free and media-direct-dispensing inkjet bioprinter. In the present study, in addition to conventional viability assessments, we evaluated the gene expression using RNA-seq to investigate whether the developed bioprinter influenced cell integrity in mouse embryonic stem cells. We evaluated the developed bioprinter based on three dispensing methods: manual operation using a micropipette, FACS and the developed inkjet bioprinter. According to the results, the developed inkjet bioprinter exhibited cell-friendly dispensing performance, which was similar to the manual dispensing operation, based not only on cell viability but also on gene expression levels.

Effective microtissue RNA extraction coupled with Smart-seq2 for reproducible and robust spatial transcriptome analysis.

Spatial transcriptomics is useful for understanding the molecular organization of a tissue and providing insights into cellular function in a morphological context. In order to obtain reproducible results in spatial transcriptomics, we have to maintain tissue morphology and RNA molecule stability during the image acquisition and biomolecule collection processes. Here, we developed a tissue processing method for robust and reproducible RNA-seq from tissue microdissection samples. In this method, we suppressed RNA degradation in fresh-frozen tissue specimens by dehydration fixation and effectively collected a small amount of RNA molecules from microdissection samples by magnetic beads. We demonstrated the spatial transcriptome analysis of the mouse liver and brain in serial microdissection samples (100 µm in a diameter and 10 µm in thickness) produced by a microdissection punching system. Using our method, we could prevent RNA degradation at room temperature and effectively produce a sequencing library with Smart-seq2. This resulted in reproducible sequence read mapping in exon regions and the detection of more than 2000 genes compared to non-fixed samples in the RNA-seq analysis. Our method would be applied to various transcriptome analyses, providing the information for region specific gene expression in tissue specimens.

Sequential Sensing by TLR2 and Mincle Directs Immature Myeloid Cells to Protect against Invasive Group A Streptococcal Infection in Mice.

Severe invasive group A Streptococcus (GAS) infection evades anti-bacterial immunity by attenuating the cellular components of innate immune responses. However, this loss of protection is compensated for by interferon (IFN)-γ-producing immature myeloid cells (γIMCs), which are selectively recruited upon severe invasive GAS infection in mice. Here, we demonstrate that γIMCs provide this IFN-γ-mediated protection by sequentially sensing GAS through two distinct pattern recognition receptors. In a mouse model, GAS is initially recognized by Toll-like receptor 2 (TLR2), which promptly induces interleukin (IL)-6 production in γIMCs. γIMC-derived IL-6 promotes the upregulation of a recently identified GAS-sensing receptor, macrophage-inducible C-type lectin (Mincle), in an autocrine or paracrine manner. Notably, blockade of γIMC-derived IL-6 abrogates Mincle expression, downstream IFN-γ production, and γIMC-mediated protection against severe invasive GAS infection. Thus, γIMCs regulate host protective immunity against severe invasive GAS infection via a TLR2-IL-6-Mincle axis.

Vertical flow array chips reliably identify cell types from single-cell mRNA sequencing experiments.

Single-cell mRNA sequencing offers an unbiased approach to dissecting cell types as functional units in multicellular tissues. However, highly reliable cell typing based on single-cell gene expression analysis remains challenging because of the lack of methods for efficient sample preparation for high-throughput sequencing and evaluating the statistical reliability of the acquired cell types. Here, we present a highly efficient nucleic reaction chip (a vertical flow array chip (VFAC)) that uses porous materials to reduce measurement noise and improve throughput without a substantial increase in reagent. We also present a probabilistic evaluation method for cell typing depending on the amount of measurement noise. Applying the VFACs to 2580 monocytes provides 1967 single-cell expressions for 47 genes, including low-expression genes such as transcription factors. The statistical method can distinguish two cell types with probabilistic quality values, with the measurement noise level being considered for the first time. This approach enables the identification of various sub-types of cells in tissues and provides a foundation for subsequent analyses.