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At least 127 records · Page 7

Multisensor Instrument for Real-Time Biological Monitoring

The figure schematically depicts an instrumentation system, called a fiber optic-based integration system (FOBIS), that is undergoing development to enable real-time monitoring of fluid cell cultures, bioprocess flows, and the like. The FOBIS design combines a micro flow cytometer (MFC), a microphotometer (MP), and a fluorescence-spectrum- or binding-force-measuring micro-sensor (MS) in a single instrument that is capable of measuring multiple biological parameters simultaneously or sequentially. The fiber-optic-based integration system is so named because the MFC, the MP, and the MS are integrated into a single optical system that is coupled to light sources and photometric equipment via optical fibers. The optical coupling components also include a wavelength-division multiplexer and diffractive optical elements. The FOBIS includes a laserdiode- and fiber-optic-based optical trapping subsystem (optical tweezers ) with microphotometric and micro-sensing capabilities for noninvasive confinement and optical measurement of relevant parameters of a single cell or other particle. Some of the measurement techniques implemented together by the FOBIS have long been used separately to obtain basic understanding of the optical properties of individual cells and other organisms, the optical properties of populations of organisms, and the interrelationships among these properties, physiology of the organisms, and physical processes that govern the media that surround the organisms. For example, flow cytometry yields information on numerical concentrations, cross-sectional areas, and types of cells or other particles. Micro-sensing can be used to measure pH and concentrations of oxygen, carbon dioxide, glucose, metabolites, calcium, and antigens in a cell-culture fluid, thereby providing feedback that can be helpful in improving control over a bioprocess. Microphotometry (including measurements of scattering and fluorescence) can yield further information about optically trapped individual particles. In addition to the multifunctionality not previously available in a single biological monitoring system, the FOBIS offers advantages of low mass, sensitivity, accuracy, portability, low cost, compactness (the overall dimensions of the fully developed FOBIS sensor head are expected to be less than 1 by 1 by 2 cm), and immunity to electromagnetic interference at suboptical frequencies. FOBIS could be useful in a variety of laboratory and field settings in such diverse endeavors as medical, veterinary, and general biological research; medical and veterinary diagnosis monitoring of industrial bioprocesses; and analysis of biological contaminants in air, water, and food.

Zhang, Sean (Zhanxiang)↗

Organogenetic transcriptomes of the Drosophila embryo at single cell resolution

To gain insight into the transcription programs activated during the formation of Drosophila larval structures, we carried out single cell RNA sequencing during two periods of Drosophila embryogenesis: stages 10-12, when most organs are first specified and initiate morphological and physiological specialization; and stages 13-16, when organs achieve their final mature architectures and begin to function. Our data confirm previous findings with regards to functional specialization of some organs – the salivary gland and trachea – and clarify the embryonic functions of another – the plasmatocytes. We also identify two early developmental trajectories in germ cells and uncover a potential role for proteolysis during germline stem cell specialization. We identify the likely cell type of origin for key components of the Drosophila matrisome and several commonly used Drosophila embryonic cell culture lines. Finally, we compare our findings with other recent related studies and with other modalities for identifying tissue-specific gene expression patterns. These data provide a useful community resource for identifying many new players in tissue-specific morphogenesis and functional specialization of developing organs.

59 BASIC BIOLOGICAL SCIENCES↗

IL-17A Increases Doxorubicin Efficacy in Triple Negative Breast Cancer

Due to lack of targetable receptors and intertumoral heterogeneity, triple negative breast cancer (TNBC) remains particularly difficult to treat. Doxorubicin (DOX) is typically used as nonselective neoadjuvant chemotherapy, but the diversity of treatment efficacy remains unclear. Comparable to variability in clinical response, an experimental model of TNBC using a 4T1 syngeneic mouse model was found to elicit a differential response to a seven-day treatment regimen of DOX. Single-cell RNA sequencing identified an increase in T cells in tumors that responded to DOX treatment compared to tumors that continued to grow uninhibited. Additionally, compared to resistant tumors, DOX sensitive tumors contained significantly more CD4 T helper cells (339%), γδ T cells (727%), Naïve T cells (278%), and activated CD8 T cells (130%). Furthermore, transcriptional profiles of tumor infiltrated T cells in DOX responsive tumors revealed decreased exhaustion, increased chemokine/cytokine expression, and increased activation and cytotoxic activity. γδ T cell derived IL-17A was identified to be highly abundant in the sensitive tumor microenvironment. IL-17A was also found to directly increase sensitivity of TNBC cells in combination with DOX treatment. In TNBC tumors sensitive to DOX, increased IL-17A levels lead to a direct effect on cancer cell responsiveness and chronic stimulation of tumor infiltrated T cells leading to improved chemotherapeutic efficacy. IL-17A’s role as a chemosensitive cytokine in TNBC may offer new opportunities for treating chemoresistant breast tumors and other cancer types.

4T1↗

An analysis of particle track effects on solid mammalian tissues

Relative biological effectiveness (RBE) and quality factor (Q) at extreme values of linear energy transfer (LET) have been determined on the basis of experiments with single-cell systems and specific tissue responses. In typical single-cell systems, each heavy particle (Ar or Fe) passes through a single cell or no cell. In experiments on animal tissues, however, each heavy particle passes through several cells, and the LET can exceed 200 keV micrometers-1 in every cell. In most laboratory animal tissue systems, however, only a small portion of the hit cells are capable of expressing the end-point being measured, such as cell killing, mutation or carcinogenesis. The following question was therefore addressed: do RBEs and Q factors derived from single-cell experiments properly account for the damage at high LET when multiple cells are hit by HZE tracks? A review is offered in which measured radiation effects and known tissue properties are combined to estimate on the one hand, the number of cells at risk, p3n, per track, where n is the number of cells per track based on tissue and organ geometry, and p3 is the probability that a cell in the track is capable of expressing the experimental end-point. On the other hand, the tissue and single-cell responses are compared by determining the ratio RBE in tissue/RBE in corresponding single cells. Experimental data from the literature indicate that tissue RBEs at very high LET (Fe and Ar ions) are higher than corresponding single-cell RBEs, especially in tissues in which p3n is high.

Non-NASA Center↗

Single-Cell Transcriptomic Analysis of Tumor-Derived Fibroblasts and Normal Tissue-Resident Fibroblasts Reveals Fibroblast Heterogeneity in Breast Cancer

Cancer-associated fibroblasts (CAFs) are a prominent stromal cell type in solid tumors and molecules secreted by CAFs play an important role in tumor progression and metastasis. CAFs coexist as heterogeneous populations with potentially different biological functions. Although CAFs are a major component of the breast cancer stroma, molecular and phenotypic heterogeneity of CAFs in breast cancer is poorly understood. In this study, we investigated CAF heterogeneity in triple-negative breast cancer (TNBC) using a syngeneic mouse model, BALB/c-derived 4T1 mammary tumors. Using single-cell RNA sequencing (scRNA-seq), we identified six CAF subpopulations in 4T1 tumors including: 1) myofibroblastic CAFs, enriched for α-smooth muscle actin and several other contractile proteins; 2) ‘inflammatory’ CAFs with elevated expression of inflammatory cytokines; and 3) a CAF subpopulation expressing major histocompatibility complex (MHC) class II proteins that are generally expressed in antigen-presenting cells. Comparison of 4T1-derived CAFs to CAFs from pancreatic cancer revealed that these three CAF subpopulations exist in both tumor types. Interestingly, cells with inflammatory and MHC class II-expressing CAF profiles were also detected in normal breast/pancreas tissue, suggesting that these phenotypes are not tumor microenvironment-induced. This work enhances our understanding of CAF heterogeneity, and specifically targeting these CAF subpopulations could be an effective therapeutic approach for treating highly aggressive TNBCs.

60 APPLIED LIFE SCIENCES↗

Water hyacinths for upgrading sewage lagoons to meet advanced wastewater treatment standards, part 2

Field tests using water hyacinths as biological filtration agents were conducted in the Mississippi gulf coast region. The plants were installed in one single cell and one multiple cell sewage lagoon systems. Water hyacinths demonstrated the ability to maintain BOD5 and total suspended solid (TSS) levels within the Environmental Protection Agency's prescribed limits of 30 mg/lBOD5 and 30 mg/l TSS. A multiple cell sewage lagoon system consisting of two aerated and one water hyacinth covered cell connected in series demonstrated the ability to maintain BOD5 and TSS levels below 30 mg/l year-round. A water hyacinth covered lagoon with a surface area of 0.28 hectare containing a total volume of 6.8 million liters demonstrated the capacity to treat 437,000 to 1,893,000 liters of sewage influent from 2.65 hectares of aerated lagoons daily and produce an effluent that met or exceeded standards year-round.

Wolverton, B. C.↗

Using mechanistic models and machine learning to design single-color multiplexed nascent chain tracking experiments

mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Over the past decade, large strides in microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent chain tracking (NCT), these methods have explored many temporal dynamics in mRNA translation uncaptured by other experimental methods such as ribosomal profiling, smFISH, pSILAC, BONCAT, or FUNCAT-PLA. However, NCT is currently restricted to the observation of one or two mRNA species at a time due to limits in the number of resolvable fluorescent tags. In this work, we propose a hybrid computational pipeline, where detailed mechanistic simulations produce realistic NCT videos, and machine learning is used to assess potential experimental designs for their ability to resolve multiple mRNA species using a single fluorescent color for all species. Our simulation results show that with careful application this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a simulated example NCT experiment with seven different mRNA species within the same simulated cell and use our ML labeling to identify these spots with 90% accuracy using only two distinct fluorescent tags. We conclude that the proposed extension to the NCT color palette should allow experimentalists to access a plethora of new experimental design possibilities, especially for cell Signaling applications requiring simultaneous study of multiple mRNAs.

59 BASIC BIOLOGICAL SCIENCES↗

Plant Cell Identity in the Era of Single-Cell Transcriptomics

High-throughput single-cell transcriptomic approaches have revolutionized our view of gene expression at the level of individual cells, providing new insights into their heterogeneity, identities, and functions. Recently, technical challenges to the application of single-cell transcriptomics to plants have been overcome, and many plant organs and tissues have now been subjected to analyses at single-cell resolution. In this review, we describe these studies and their impact on our understanding of the diversity, differentiation, and activities of plant cells. We particularly highlight their impact on plant cell identity, including unprecedented views of cell transitions and definitions of rare and novel cell types. Lastly, we also point out current challenges and future opportunities for the application and analyses of single-cell transcriptomics in plants.

59 BASIC BIOLOGICAL SCIENCES↗

In-Depth Mass Spectrometry-Based Single-Cell and Nanoscale Proteomics

Leukemic stem cells are highly dynamic and heterogeneous. Analysis of leukemic stem cells at the single cell level should provide a wealth of insights that would not be possible using bulk measurements. Mass spectrometry (MS)-based proteomic workflows can quantify hundreds or thousands of proteins from a biological sample and has proven invaluable for biomedical research, but samples comprising large numbers of cells are typically required due to limited sensitivity. Recent developments in sample processing, chromatographic separations and MS instrumentation are now extending in-depth proteome profiling to single mammalian cells. We describe specific techniques that increase the sensitivity of single-cell proteomics by orders of magnitude, enabling the promise of single cell proteomics to become a reality. We anticipate such techniques could significantly advance our understanding of leukemic stem cells.

Liang, Yiran↗

Single-molecule 3D imaging of HIV cellular entry by liquid-phase electron tomography

Enveloped viruses, including human immunodeficiency virus (HIV) and SARS-CoV-2, target cells through membrane fusion process. The detailed understanding of the process is sought after for vaccine development but remains elusive due to current technique limitations for direct three-dimensional (3D) imaging of an individual virus during its viral entry. Recently, we developed a simple specimen preparation method for real-time imaging of metal dynamic liquid-vaper interface at nanometer resolution by transmission electron microscopy (TEM). Here, we extended this method to study biology sample through snapshot 3D structure of a single HIV (pseudo-typed with the envelope glycoprotein of vesicular stomatitis virus, VSV-G) at its intermediate stage of viral entry to HeLa cells in a liquid-phase environment. By individual-particle electron tomography (IPET), we found the viral surface release excess lipids with unbound viral spike proteins forming ~50-nm nanoparticles instead of merging cell membrane. Moreover, the spherical-shape shell formed by matrix proteins underneath the viral envelope does not disassemble into a cone shape right after fusion. Further, the snapshot 3D imaging of a single virus provides us a direct structure-based understanding of the viral entry mechanism, which can be used to examine other viruses to support the development of vaccines combatting the current ongoing pandemic.

Kong, Lingli↗

GAL08, an Uncultivated Group of Acidobacteria, Is a Dominant Bacterial Clade in a Neutral Hot Spring

GAL08 are bacteria belonging to an uncultivated phylogenetic cluster within the phylum Acidobacteria . We detected a natural population of the GAL08 clade in sediment from a pH-neutral hot spring located in British Columbia, Canada. To shed light on the abundance and genomic potential of this clade, we collected and analyzed hot spring sediment samples over a temperature range of 24.2–79.8°C. Illumina sequencing of 16S rRNA gene amplicons and qPCR using a primer set developed specifically to detect the GAL08 16S rRNA gene revealed that absolute and relative abundances of GAL08 peaked at 65°C along three temperature gradients. Analysis of sediment collected over multiple years and locations revealed that the GAL08 group was consistently a dominant clade, comprising up to 29.2% of the microbial community based on relative read abundance and up to 4.7 × 10 5 16S rRNA gene copy numbers per gram of sediment based on qPCR. Using a medium quality threshold, 25 single amplified genomes (SAGs) representing these bacteria were generated from samples taken at 65 and 77°C, and seven metagenome-assembled genomes (MAGs) were reconstructed from samples collected at 45–77°C. Based on average nucleotide identity (ANI), these SAGs and MAGs represented three separate species, with an estimated average genome size of 3.17 Mb and GC content of 62.8%. Phylogenetic trees constructed from 16S rRNA gene sequences and a set of 56 concatenated phylogenetic marker genes both placed the three GAL08 bacteria as a distinct subgroup of the phylum Acidobacteria , representing a candidate order ( Ca. Frugalibacteriales) within the class Blastocatellia. Metabolic reconstructions from genome data predicted a heterotrophic metabolism, with potential capability for aerobic respiration, as well as incomplete denitrification and fermentation. In laboratory cultivation efforts, GAL08 counts based on qPCR declined rapidly under atmospheric levels of oxygen but increased slightly at 1% (v/v) O 2 , suggesting a microaerophilic lifestyle.

59 BASIC BIOLOGICAL SCIENCES↗

Characterizing the Self-Assembly Properties of Monoolein Lipid Isosteres

Living cells feature lipid compartments which exhibit a variety of shapes and structures that assist essential cellular processes. Many natural cell compartments frequently adopt convoluted nonlamellar lipid architectures that facilitate specific biological reactions. Improved methods for controlling the structural organization of artificial model membranes would facilitate investigations into how membrane morphology affects biological functions. Monoolein (MO) is a single-chain amphiphile which forms nonlamellar lipid phases in aqueous solution and has wide applications in nanomaterial development, the food industry, drug delivery, and protein crystallization. However, even if MO has been extensively studied, simple isosteres of MO, while readily accessible, have seen limited characterization. An improved understanding of how relatively minor changes in lipid chemical structure affect self assembly and membrane topology could instruct the construction of artificial cells and organelles for modeling biological structures and facilitate nanomaterial-based applications. Here, we investigate the differences in self-assembly and large-scale organization between MO and two MO lipid isosteres. We show that replacing the ester linkage between the hydrophilic headgroup and hydrophobic hydrocarbon chain with a thioesther or amide functional group results in the assembly of lipid structures with different phases not resembling those formed by MO. Using light and cryo-electron microscopy, small-angle X-ray scattering, and infrared spectroscopy, we demonstrate differences in the molecular ordering and large-scale architectures of the self-assembled structures made from MO and its isosteric analogues. These results improve our understanding of the molecular underpinnings of lipid mesophase assembly and may facilitate the development of MO-based materials for biomedicine and as model lipid compartments.

60 APPLIED LIFE SCIENCES↗

CrossMP: Enabling Cross-Modality Translation between Single-Cell RNA-Seq and Single-Cell ATAC-Seq through Web-Based Portal

In recent years, there has been a growing interest in profiling multiomic modalities within individual cells simultaneously. One such example is integrating combined single-cell RNA sequencing (scRNA-seq) data and single-cell transposase-accessible chromatin sequencing (scATAC-seq) data. Integrated analysis of diverse modalities has helped researchers make more accurate predictions and gain a more comprehensive understanding than with single-modality analysis. However, generating such multimodal data is technically challenging and expensive, leading to limited availability of single-cell co-assay data. Here, we propose a model for cross-modal prediction between the transcriptome and chromatin profiles in single cells. Our model is based on a deep neural network architecture that learns the latent representations from the source modality and then predicts the target modality. It demonstrates reliable performance in accurately translating between these modalities across multiple paired human scATAC-seq and scRNA-seq datasets. Additionally, we developed CrossMP, a web-based portal allowing researchers to upload their single-cell modality data through an interactive web interface and predict the other type of modality data, using high-performance computing resources plugged at the backend.

59 BASIC BIOLOGICAL SCIENCES↗

Constraining the composition and quantity of organic matter used by abundant marine Thaumarchaeota

Marine Group I (MGI) Thaumarchaeota were originally described as chemoautotrophic nitrifiers, but molecular and isotopic evidence suggests heterotrophic and/or mixotrophic capabilities. Here, in this study, we investigated the quantity and composition of organic matter assimilated by individual, uncultured MGI cells from the Pacific Ocean to constrain their potential for mixotrophy and heterotrophy. We observed that most MGI cells did not assimilate carbon from any organic substrate provided (glucose, pyruvate, oxaloacetate, protein, urea, and amino acids). The minority of MGI cells that did assimilate it did so exclusively from nitrogenous substrates (urea, 15% of MGI and amino acids, 36% of MGI), and only as an auxiliary carbon source (<20% of that subset's total cellular carbon was derived from those substrates). At the population level, MGI assimilation of organic carbon comprised just 0.5%–11% of total biomass carbon. We observed extensive assimilation of inorganic carbon and urea- and amino acid-derived nitrogen (equal to that from ammonium), consistent with metagenomic and metatranscriptomic analyses performed here and previously showing a widespread potential for MGI to perform autotrophy and transport and degrade organic nitrogen. Our results constrain the quantity and composition of organic matter used by MGI and suggest they use it primarily to meet nitrogen demands for anabolism and nitrification.

13C↗

First Plant Cell Atlas symposium report

The Plant Cell Atlas (PCA) community hosted a virtual symposium on December 9 and 10, 2021 on single cell and spatial omics technologies. The conference gathered almost 500 academic, industry, and government leaders to identify the needs and directions of the PCA community and to explore how establishing a data synthesis center would address these needs and accelerate progress. This report details the presentations and discussions focused on the possibility of a data synthesis center for a PCA and the expected impacts of such a center on advancing science and technology globally. Community discussions focused on topics such as data analysis tools and annotation standards; computational expertise and cyber-infrastructure; modes of community organization and engagement; methods for ensuring a broad reach in the PCA community; recruitment, training, and nurturing of new talent; and the overall impact of the PCA initiative. These targeted discussions facilitated dialogue among the participants to gauge whether PCA might be a vehicle for formulating a data synthesis center. The conversations also explored how online tools can be leveraged to help broaden the reach of the PCA (i.e., online contests, virtual networking, and social media stakeholder engagement) and decrease costs of conducting research (e.g., virtual REU opportunities). Major recommendations for the future of the PCA included establishing standards, creating dashboards for easy and intuitive access to data, and engaging with a broad community of stakeholders. The discussions also identified the following as being essential to the PCA's success: identifying homologous cell-type markers and their biocuration, publishing datasets and computational pipelines, utilizing online tools for communication (such as Slack), and user-friendly data visualization and data sharing. In conclusion, the development of a data synthesis center will help the PCA community achieve these goals by providing a centralized repository for existing and new data, a platform for sharing tools, and new analytical approaches through collaborative, multidisciplinary efforts. A data synthesis center will help the PCA reach milestones, such as community-supported data evaluation metrics, accelerating plant research necessary for human and environmental health.

59 BASIC BIOLOGICAL SCIENCES↗