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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

A comparison of RNA with DNA in template-directed synthesis

Nonenzymatic template-directed copying of RNA sequences rich in cytidylic acid using nucleoside 5'-(2-methylimidazol-1-yl phosphates) as substrates is substantially more efficient than the copying of corresponding DNA sequences. However, many sequences cannot be copied, and the prospect of replication in this system is remote, even for RNA. Surprisingly, wobble-pairing leads to much more efficient incorporation of G opposite U on RNA templates than of G opposite T on DNA templates.

Non-NASA Center↗
NASA NTRS1993

An RNA motif that binds ATP

RNAs that contain specific high-affinity binding sites for small molecule ligands immobilized on a solid support are present at a frequency of roughly one in 10(10)-10(11) in pools of random sequence RNA molecules. Here we describe a new in vitro selection procedure designed to ensure the isolation of RNAs that bind the ligand of interest in solution as well as on a solid support. We have used this method to isolate a remarkably small RNA motif that binds ATP, a substrate in numerous biological reactions and the universal biological high-energy intermediate. The selected ATP-binding RNAs contain a consensus sequence, embedded in a common secondary structure. The binding properties of ATP analogues and modified RNAs show that the binding interaction is characterized by a large number of close contacts between the ATP and RNA, and by a change in the conformation of the RNA.

NASA Discipline Exobiology↗
DOE OSTI2026

SEGUID v2: Extending SEGUID checksums for circular, linear, single- and double-stranded biological sequences

Background Synthetic biology involves combining different DNA fragments, each containing functional biological parts, to address specific problems. Fundamental gene-function research often requires cloning and propagating DNA fragments, such as those from the iGEM Parts Registry or Addgene, typically distributed as circular plasmids. Addgene’s repository alone offers around 150,000 plasmids. To ensure data integrity, cryptographic checksums can be calculated for the sequences. Each sequence has a unique checksum, making checksums useful for validation and quick lookups of associated annotations. For example, the SEGUID checksum uniquely identifies protein sequences with a 27-character string. Objectives The original SEGUID, while effective for protein sequences and single-stranded DNA (ssDNA), is not suitable for circular DNA since there is no natural starting position nor for double-stranded DNA (dsDNA) since two separate sequences are present. Challenges include how to uniquely represent linear dsDNA, circular ssDNA, and circular dsDNA. To meet these needs, we propose SEGUID v2, which extends the original SEGUID to handle additional types of sequences. Conclusions SEGUID v2 produces orientation and rotation invariant checksums for single-stranded, double-stranded, possibly staggered, linear, and circular DNA and RNA sequences. Customizable alphabets allow for other types of sequences. In contrast to the original SEGUID, which uses Base64, SEGUID v2 uses Base64url to encode the SHA-1 hash. This ensures SEGUID v2 checksums can be used as-is in filenames, regardless of platform, and in URLs, with minimal friction. Availability SEGUID v2 is readily available for major programming languages, distributed under the MIT license. JavaScript package seguid is available on npm, Python package seguid on PyPi, R package seguid on CRAN, and a Tcl script on GitHub. These tools, along with documentation, examples, and an online SEGUID Calculator , can be found at https://www.seguid.org .

Pereira, Humberto↗
NASA NTRS1989

The Deinococcus-Thermus phylum and the effect of rRNA composition on phylogenetic tree construction

Through comparative analysis of 16S ribosomal RNA sequences, it can be shown that two seemingly dissimilar types of eubacteria Deinococcus and the ubiquitous hot spring organism Thermus are distantly but specifically related to one another. This confirms an earlier report based upon 16S rRNA oligonucleotide cataloging studies (Hensel et al., 1986). Their two lineages form a distinctive grouping within the eubacteria that deserved the taxonomic status of a phylum. The (partial) sequence of T. aquaticus rRNA appears relatively close to those of other thermophilic eubacteria. e.g. Thermotoga maritima and Thermomicrobium roseum. However, this closeness does not reflect a true evolutionary closeness; rather it is due to a "thermophilic convergence", the result of unusually high G+C composition in the rRNAs of thermophilic bacteria. Unless such compositional biases are taken into account, the branching order and root of phylogenetic trees can be incorrectly inferred.

Non-NASA Center↗
NASA NTRS1987

The green non-sulfur bacteria: a deep branching in the eubacterial line of descent

Ribosomal RNA sequence comparisons define a phylogenetic grouping, the green non-sulfur bacteria and relatives (GNS), known to contain the genera Chloroflexus, Herpetosiphon and Thermomicrobium--organisms that have little phenotypic similarity. The unit is phylogenetically deep, but entirely distinct from any other eubacterial division (phylum). It is also relatively ancient--branching from the common eubacterial stem earlier than any other group of eubacteria reported thus far. The group phenotype is predominantly thermophilic, and its thermophilic members, especially Thermomicrobium, are more slowly evolving than Herpetosiphon, a mesophile. The GNS unit appears significantly older than either the green sulfur bacteria or the cyanobacteria--making it likely that organisms such as Chloroflexus, not the cyanobacteria, generated the oldest stromatolites, which formed over three billion years ago.

Non-NASA Center↗
NASA NTRS2000

Models of the Protocellular Structures, Functions and Evolution

In the absence of extinct or extant record of protocells, the most direct way to test our understanding of the origin of cellular life is to construct laboratory models that capture important features of protocellular systems. Such efforts are currently underway in a collaborative project between NASA-Ames, Harvard medical School and University of California. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures. The centerpiece of this project is a method for the in vitro evolution of protein enzymes toward arbitrary catalytic targets. A similar approach has already been developed for nucleic acids: First, a very large population of candidate molecules is generated using a random synthetic approach. Next, the small numbers of molecules that can accomplish the desired task are selected. These molecules are next vastly multiplied using the polymerase chain reaction. A mutagenic approach, in which the sequences of selected molecules are randomly altered, can yield further improvements in performance or alterations of specificities. Unfortunately, the catalytic potential of nucleic acids is rather limited. Proteins are more catalytically capable but cannot be directly amplified. In the new technique, this problem is circumvented by covalently linking each protein of the initial, diverse, pool to the RNA sequence that codes for it. Then, selection is performed on the proteins, but the nucleic acids are replicated. To date, we have obtained "a proof of concept" by evolving simple, novel proteins capable of selectively binding adenosine tri-phosphate (ATP). Our next goal is to create an enzyme that can phosphorylate amino acids and another to catalyze the formation of peptide bonds in the absence of nucleic acid templates. This latter reaction does not take place in contemporary cells. once developed, these enzymes will be encapsulated in liposomes so that they will function in a simulated cellular environment. To provide a continuous energy supply, usually needed to activate the substrates, an energy transduction complex which generates ATP from adenosine diphosphate, inorganic phosphate and light will be used. This system, consisting of two modern proteins, ATP synthase and bacteriorhodopsin, has already been built and shown to work efficiently. By coupling chemical synthesis to such a system, it will be possible to drive chemical reactions by light if only the substrates for these reactions are supplied.

Pohorille, Andrew↗
NASA NTRS2001

Models of Protocellular Structure, Function and Evolution

In the absence of any record of protocells, the most direct way to test our understanding of the origin of cellular life is to construct laboratory models that capture important features of protocellular systems. Such efforts are currently underway in a collaborative project between NASA-Ames, Harvard Medical School and University of California. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures. The centerpiece of this project is a method for the in vitro evolution of protein enzymes toward arbitrary catalytic targets. A similar approach has already been developed for nucleic acids in which a small number of functional molecules are selected from a large, random population of candidates. The selected molecules are next vastly multiplied using the polymerase chain reaction. A mutagenic approach, in which the sequences of selected molecules are randomly altered, can yield further improvements in performance or alterations of specificities. Unfortunately, the catalytic potential of nucleic acids is rather limited. Proteins are more catalytically capable but cannot be directly amplified. In the new technique, this problem is circumvented by covalently linking each protein of the initial, diverse, pool to the RNA sequence that codes for it. Then, selection is performed on the proteins, but the nucleic acids are replicated. Additional information is contained in the original extended abstract.

New, Michael H.↗
DOE OSTI2025

scRNA seq of an F1 cross of Marek’s disease resistant and susceptible chickens identifies allele specific expression signatures enriched in transcription modulators

Abstract Marek’s disease (MD), a T cell lymphoma disease in chickens, is caused by the Marek’s disease virus (MDV) found ubiquitously in the poultry industry. Genetically resistant Line 6 3 (L6) and susceptible Line 7 2 (L7) chickens have been instrumental to research on avian immune system response to MDV infection. In this study we characterized molecular signatures unique to splenic immune cell types across different genetic backgrounds 6 days after infection. Using three populations, L6, L7, and an F1 cross between L6xL7, we evaluated the immune cell transcriptome of responding cell types using single cell RNA sequencing. Several MDV genes were found expressed mainly in cytotoxic T cells while ICP4 and MEQ MDV genes were expressed across infected cell types. Using the F1 we quantified allele specific expression (ASE) of biallelic SNPs and found biased expression of parental alleles specific to immune cell subtypes. We identified 22 SNPs with ASE in response to MDV infection mapped to gene rich regions surrounding 59 genes of critical importance for chromatin remodeling and transcriptional regulation. Histone deacetylase genes (HDAC1 and HDAC8) had increased expression of L6 alleles, while small nuclear RNA genes (SNORA68 and SNORA72) expressed higher levels of L7 alleles with infection in T cell subsets. SNPs with ASE also mapped genes important for an adequate immune response including GNLY (cytotoxic activity) and PDIA3 (component of MHC class I peptide loading complex), and genes known to promote viral replication (MCM5 and EIF3M). These results show that functional variants associated with susceptibility to MD may have a bigger impact in subsets of immune cell types, and by characterizing the transcriptomes of these subtypes we can unravel molecular signatures specific to MD genomic resistance.

Science & Technology - Other Topics↗
NASA NTRS1994

Characterization of a new thermophilic sulfate-reducing bacterium Thermodesulfovibrio yellowstonii, gen. nov. and sp. nov.: its phylogenetic relationship to Thermodesulfobacterium commune and their origins deep within the bacterial domain

A thermophilic sulfate-reducing vibrio isolated from thermal vent water in Yellowstone Lake, Wyoming, USA is described. The gram-negative, curved rod-shaped cells averaged 0.3 micrometer wide and 1.5 micrometers long. They were motile by means of a single polar flagellum. Growth was observed between 40 degrees and 70 degrees C with optimal growth at 65 degrees C. Cultures remained viable for one year at 27 degrees C although spore-formation was not observed. Sulfate, thiosulfate and sulfite were used as electron acceptors. Sulfur, fumarate and nitrate were not reduced. In the presence of sulfate, growth was observed only with lactate, pyruvate, hydrogen plus acetate, or formate plus acetate. Pyruvate was the only compound observed to support fermentative growth. Pyruvate and lactate were oxidized to acetate. Desulfofuscidin and c-type cytochromes were present. The G + C content was 29.5 mol%. The divergence in the 16 S ribosomal RNA sequences between the new isolate and Thermodesulfobacterium commune suggests that these two thermophilic sulfate-reducing bacteria represent different genera. These two bacteria depict a lineage that branches deeply within the Bacteria domain and which is clearly distinct from previously defined phylogenetic lines of sulfate-reducing bacteria. Strain YP87 is described as the type strain of the new genus and species Thermodesulfovibrio yellowstonii.

Non-NASA Center↗
NASA NTRSDate not supplied

Optimizing a Small RNAseq Analysis Pipeline for NASA GeneLab Using Open-Source Tools and Libraries

Small RNA sequencing (small RNAseq) is a powerful tool for studying the regulation of gene expression in various organisms. Small RNAseq has been leveraged in space biology research to study how expression of small RNAs, e.g. micro RNAs (miRNAs), small interfering RNAs (siRNAs), and piwi-interacting RNAs (piRNAs), change upon exposure to the space environment. NASA GeneLab currently hosts small RNAseq raw data derived from space-relevant experiments on the Open Science Data Repository (OSDR). To maximize the accessibility of these data to the scientific community, in addition to hosting raw data, which is only interpretable by bioinformaticians, GeneLab plans to process all small RNAseq datasets and make those processed data available to the scientific community via the OSDR. In this study, we present the development of the GeneLab standardized pipeline for processing small RNAseq datasets. Using human, plant, and synthetic small RNAseq datasets, we interrogate various open-source software and publicly available databases to evaluate their accuracy and reproducibility in each step of the pipeline. For quality control and adapter detection and trimming, we evaluated TrimGalore!, FASTX, SeqKit, and DNApi methods to optimize alignment to reference genomes. We compared BWA, Bowtie, and Bowtie2 to determine the optimal alignment tool. For each alignment tool we also assessed various reference databases, including Ensembl reference genomes and different types of small RNA reference databases, including genome, hairpin, and miRNA references from the miRbase and MirGeneDB databases. To quantify the aligned data, we compared SAMtools, HTSeq, and RSEM for counting alignment events from each alignment tool used. Finally, we evaluated various tools, including DESeq2 and EdgeR, for data normalization and subsequent differential expression analysis. We will present the results from our comparative analyses for each pipeline step and propose a consensus pipeline for processing small RNAseq data derived from various organisms exposed to the space environment.

SmallRNAseq, NASA GeneLab, quality control, adapte↗
DOE OSTI2026

Host analysis-guided selection and targeted engineering (HASTE) of Lipomyces tetrasporus for the conversion of CO2-derived feedstocks

Efficient and cost-competitive bioproduction calls for utilizing CO2-derived feedstocks, such as products from electro-reduction of CO2 and hydrolysate from lignocellulosic biomass. However, efficiently using all their carbon components, including acetate, glucose, and xylose, remains a challenge. Here, we characterize Lipomyces tetrasporus, a novel, robust yeast strain capable of effectively assimilating these carbon sources. We used an integrated systems biology approach combining ¹³C metabolic flux analysis, dynamic labeling experiments, and RNA sequencing. We conducted the first metabolic flux analysis for glucose, xylose, and acetate catabolism in this species. Dynamic labeling revealed a highly active TCA cycle during acetate metabolism, evidenced by rapid citrate and malate accumulation. The strain demonstrated strong NADH/NADPH production and acetyl-CoA synthase activity. Using insights and gene targets from this analysis, we engineered L. tetrasporus for malate production. The engineered strain produced 7.5 g/L malic acid (0.25 g/g yield) in shake flasks with glucose-acetate media and 28.8 g/L malic acid at a yield of 0.20 g/g in fed-batch mode with corn-stover hydrolysate. Together, these insights and rational strain engineering establish L. tetrasporus as a versatile, Crabtree-negative platform that is an energy-CO2-bioproduction nexus for channeling CO2 carbon into value-added bioproducts.

Xiao, Zhengyang↗
DOE OSTI2026

scPlantAnnotate: an accurate and robust transformer-based model for plant cell type annotation

Accurate cell type annotation remains a major bottleneck in plant single-cell RNA sequencing (scRNA-seq), where existing tools are often adapted from animal studies and perform sub-optimally on plant data. The lack of plant-specific computational frameworks limits the construction of plant cell atlases and downstream biological discovery. We develop and evaluate scPlantAnnotate, a Transformer-based reference annotation framework tailored for plant scRNA-seq data, and benchmark it against state-of-the-art deep learning and conventional methods across multiple plant species. Species-specific scPlantAnnotate models were trained using curated datasets from Arabidopsis thaliana, Zea mays, Oryza sativa, and Glycine max. We compared scPlantAnnotate with leading baselines under both standard random-split evaluation and a more stringent leave-one-dataset-out setting, which tests robustness to completely unseen datasets and tissue types. scPlantAnnotate consistently outperforms existing approaches across all four species under random-split evaluation. In the leave-one-dataset-out setting for A. thaliana, where performance drops markedly for all methods due to strong batch effects and dataset heterogeneity, scPlantAnnotate nonetheless achieves the highest Accuracy, Macro-F1, Balanced Accuracy, and Macro-AUROC on average and ranks first on most held-out datasets. These results demonstrate improved robustness to dataset shifts, a critical yet underexplored challenge in plant scRNA-seq analysis. A freely accessible web server enables users to annotate their own datasets using pretrained models. scPlantAnnotate provides a plant-specific, Transformer-based framework for single-cell annotation that delivers state-of-the-art performance and enhanced robustness to unseen datasets. By addressing limitations of existing tools and enabling scalable reference-based annotation, scPlantAnnotate supports the development of comprehensive plant cell atlases and facilitates broader use of single-cell genomics in plant biology.

Bioinformatics↗
DOE OSTI2025

Cerebellar dysfunction in a mouse model of childhood-onset manganese-induced dystonia parkinsonism

Humans with pathogenic variants of the manganese (Mn) transporter gene SLC39A14 exhibit highly elevated brain Mn concentrations and childhood-onset dystonia-parkinsonism. Here we show that Slc39a14-knockout (KO) mice, a preclinical model of the disease with elevated Mn concentrations in the CB, express deficits in physiological tremor implicating cerebellar (CB) dysfunction. Imaging of intracellular Mn in Purkinje cells (PCs) using synchrotron-based X-ray fluorescence microscopy confirmed highly elevated Mn concentrations in the PCs of Slc39a14-KO mice. To determine biological pathways altered in the CB of Slc39a14-KO mice relative to wildtype (WT), we performed RNA sequencing and discovered significant upregulation of pathways and genes regulating immune response and cell death. To substantiate these findings, we performed quantitative autoradiography of the neuroinflammation biomarker Translocator Protein 18 kDa (TSPO) which was significantly increased in the CB of Slc39a14-KO mice relative to WT. The latter findings were confirmed via immunostaining with the microglial marker Iba-1, revealing widespread microglia activation and clustering in the CB cortex. Immunostaining for cleaved caspase-3 (cCASP3), a marker of apoptosis, showed increased number of PCs with positive immunolabeling for cCASP3 in Slc39a14-KO mice relative to WT. Degeneration of PCs was confirmed by Hematoxylin and Eosin (H&E) staining. Lastly, functional electrophysiological assessment of CB neurocircuitry revealed a marked decrease in firing rates of cerebellar nuclei (CN) neurons and increased variability of PC simple spikes firing. Collectively, these findings show, for the first time, Mn-induced PC degeneration and dysfunctional CB circuitry in Slc39a14-KO mice providing additional evidence for the pathological underpinnings of the dystonia-like movements, balance, and gait abnormalities in SLC39A14 mutation carriers.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Elucidation of odd-chain dicarboxylate metabolism in Acinetobacter baylyi and application to polyethylene upcycling

Polyethylene (PE) is a versatile polymer, but its end-of-life management is challenging due to its recalcitrant structure. We present a promising approach combining chemical degradation and bio-upcycling to convert postconsumer PE waste into a value-added bioproduct. Specifically, PE was degraded into acetic acid and C 4 –C 7 dicarboxylic acids by nitric acid. We then elucidated the catabolic pathways for glutarate (C 5 ) and pimelate (C 7 ) in the nonmodel bacterium Acinetobacter baylyi ADP1 through RNA sequencing, phenotyping, and enzymatic assays. Whole-genome sequencing of evolved isolates also identified a crucial IclR family transcriptional regulator, DcaS, which acts as a repressor of dicarboxylate metabolism. The reverse-engineered strain exhibited enhanced substrate utilization compared to the wild-type strain. Using rational metabolic engineering, the PE deconstruction products were bioconverted into the valuable chemical lycopene, highlighting the potential of this microbial chassis to produce value-added bioproducts from postconsumer PE waste, thus promoting a circular economy for plastics.

metabolic engineering↗
DOE OSTI2024

Complex transcriptional regulations of a hyperparasitic quadripartite system in giant viruses infecting protists

Abstract Hyperparasitism is a common pattern in nature that is not limited to cellular organisms. Giant viruses infecting protists can be hyperparasitized by smaller ones named virophages. In addition, both may carry episomal DNA molecules known as transpovirons in their particles. They all share transcriptional regulatory elements that dictate the expression of their genes within viral factories built by giant viruses in the host cytoplasm. This suggests the existence of interactions between their respective transcriptional networks. Here we investigatedAcanthamoeba castellaniicells infected by a giant virus (megavirus chilensis), and coinfected with a virophage (zamilon vitis) and/or a transpoviron (megavirus vitis transpoviron). Infectious cycles were monitored through time-course RNA sequencing to decipher the transcriptional program of each partner and its impact on the gene expression of the others. We found highly diverse transcriptional responses. While the giant virus drastically reshaped the host cell transcriptome, the transpoviron had no effect on the gene expression of any of the players. In contrast, the virophage strongly modified the giant virus gene expression, albeit transiently, without altering the protein composition of mature viral particles. The virophage also induced the overexpression of transpoviron genes, likely through the indirect upregulation of giant virus-encoded transcription factors. Together, these analyses document the intricated transcriptionally regulated networks taking place in the infected cell.

Science & Technology - Other Topics↗
DOE OSTI2025

Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putida

Abstract The genome-scale model of metabolism and gene expression (ME-model) forPseudomonas putidaKT2440,iPpu1676-ME, provides a comprehensive representation of biosynthetic costs and proteome allocation. Compared to a metabolic-only model,iPpu1676-ME significantly expands on gene expression, macromolecular assembly, and cofactor utilization, enabling accurate growth predictions without additional constraints. Multi-omics analysis using RNA sequencing and ribosomal profiling data revealed translational prioritization inP. putida, with core pathways, such as nicotinamide biosynthesis and queuosine metabolism, exhibiting higher translational efficiency, while secondary pathways displayed lower priority. Notably, the ME-model significantly outperformed the M-model in alignment with multi-omics data, thereby validating its predictive capacity. Thus,iPpu1676-ME offers valuable insights intoP. putida’s proteome allocation and presents a powerful tool for understanding resource allocation in this industrially relevant microorganism.

Mathematical & Computational Biology↗
DOE OSTI2025

Discovery of FoTO1 and Taxol genes enables biosynthesis of baccatin III

Abstract Plants make complex and potent therapeutic molecules 1,2 , but sourcing these molecules from natural producers or through chemical synthesis is difficult, which limits their use in the clinic. A prominent example is the anti-cancer therapeutic paclitaxel (sold under the brand name Taxol), which is derived from yew trees (Taxusspecies) 3 . Identifying the full paclitaxel biosynthetic pathway would enable heterologous production of the drug, but this has yet to be achieved despite half a century of research 4 . WithinTaxus’ large, enzyme-rich genome 5 , we suspected that the paclitaxel pathway would be difficult to resolve using conventional RNA-sequencing and co-expression analyses. Here, to improve the resolution of transcriptional analysis for pathway identification, we developed a strategy we term multiplexed perturbation × single nuclei (mpXsn) to transcriptionally profile cell states spanning tissues, cell types, developmental stages and elicitation conditions. Our data show that paclitaxel biosynthetic genes segregate into distinct expression modules that suggest consecutive subpathways. These modules resolved seven new genes, allowing a de novo 17-gene biosynthesis and isolation of baccatin III, the industrial precursor to Taxol, inNicotiana benthamianaleaves, at levels comparable with the natural abundance inTaxusneedles. Notably, we found that a nuclear transport factor 2 (NTF2)-like protein, FoTO1, is crucial for promoting the formation of the desired product during the first oxidation, resolving a long-standing bottleneck in paclitaxel pathway reconstitution. Together with a new β-phenylalanine-CoA ligase, the eight genes discovered here enable the de novo biosynthesis of 3’-N-debenzoyl-2’-deoxypaclitaxel. More broadly, we establish a generalizable approach to efficiently scale the power of co-expression analysis to match the complexity of large, uncharacterized genomes, facilitating the discovery of high-value gene sets.

Science & Technology - Other Topics↗
DOE OSTI2026

High-throughput Single-Cell Proteomics and Transcriptomics from the Same Cells with a Nanoliter-Scale Spin-Transfer Approach

Single-cell multiomic platforms provide a comprehensive snapshot of cellular states and cell types by offering critical insights into the spatiotemporal regulation of biomolecular networks at a systems level, thereby defining the basis of multicellularity. Here, we introduce nanoSPINS, an advanced platform that enables high-throughput profiling and integrative analysis of the transcriptome and proteome from the same single cells using RNA sequencing and isobaric labeling LC-MS-based proteomics, respectively. NanoSPINS can efficiently transfer mRNA-containing droplets across two microarrays via a centrifugation-based approach, while proteins are retained on the initial platform. Benchmarking of nanoSPINS on two cell lines demonstrates its ability to generate global proteomic and transcriptomic profiles that align well with previously established methodologies/platforms. The incorporation of isobaric TMTpro labeling into this single-cell multiomics platform significantly enhances the throughput of single-cell proteomic analyses. Through the high-throughput quantification of the proteome and transcriptome, nanoSPINS not only facilitates the identification of molecular features at both mRNA and protein level but also provides larger sample sizes for improved statistical power in clustering and differential abundance. Given the broad applicability of single-cell multiomics in biological research and clinical settings, we believe nanoSPINS represents a powerful platform for the characterization of heterogeneous cell populations.

multi 'omics↗