Mapping the transcriptional landscape of human white and brown adipogenesis using single-nuclei RNA-seq.

Adipogenesis is key to maintaining organism-wide energy balance and healthy metabolic phenotype, making it critical to thoroughly comprehend its molecular regulation in humans. By single-nuclei RNA-sequencing (snRNA-seq) of over 20,000 differentiating white and brown preadipocytes, we constructed a high-resolution temporal transcriptional landscape of human white and brown adipogenesis. White and brown preadipocytes were isolated from a single individual's neck region, thereby eliminating inter-subject variability across two distinct lineages. These preadipocytes were also immortalized to allow for controlled, in vitro differentiation, allowing sampling of distinct cellular states across the spectrum of adipogenic progression. Pseudotemporal cellular ordering revealed the dynamics of ECM remodeling during early adipogenesis, and lipogenic/thermogenic response during late white/brown adipogenesis. Comparison with adipogenic regulation in murine models Identified several novel transcription factors as potential targets for adipogenic/thermogenic drivers in humans. Among these novel candidates, we explored the role of TRPS1 in adipocyte differentiation and showed that its knockdown impairs white adipogenesis in vitro. Key adipogenic and lipogenic markers revealed in our analysis were applied to analyze publicly available scRNA-seq datasets; these confirmed unique cell maturation features in recently discovered murine preadipocytes, and revealed inhibition of adipogenic expansion in humans with obesity. Overall, our study presents a comprehensive molecular description of both white and brown adipogenesis in humans and provides an important resource for future studies of adipose tissue development and function in both health and metabolic disease state.

Characterization of transcript enrichment and detection bias in single-nucleus RNA-seq for mapping of distinct human adipocyte lineages.

Single-cell RNA sequencing (scRNA-seq) enables molecular characterization of complex biological tissues at high resolution. The requirement of single-cell extraction, however, makes it challenging for profiling tissues such as adipose tissue, for which collection of intact single adipocytes is complicated by their fragile nature. For such tissues, single-nucleus extraction is often much more efficient and therefore single-nucleus RNA sequencing (snRNA-seq) presents an alternative to scRNA-seq. However, nuclear transcripts represent only a fraction of the transcriptome in a single cell, with snRNA-seq marked with inherent transcript enrichment and detection biases. Therefore, snRNA-seq may be inadequate for mapping important transcriptional signatures in adipose tissue. In this study, we compare the transcriptomic landscape of single nuclei isolated from preadipocytes and mature adipocytes across human white and brown adipocyte lineages, with whole-cell transcriptome. We show that snRNA-seq is capable of identifying the broad cell types present in scRNA-seq at all states of adipogenesis. However, we also explore how and why the nuclear transcriptome is biased and limited, as well as how it can be advantageous. We robustly characterize the enrichment of nuclear-localized transcripts and adipogenic regulatory lncRNAs in snRNA-seq, while also providing a detailed understanding for the preferential detection of long genes upon using this technique. To remove such technical detection biases, we propose a normalization strategy for a more accurate comparison of nuclear and cellular data. Finally, we show successful integration of scRNA-seq and snRNA-seq data sets with existing bioinformatic tools. Overall, our results illustrate the applicability of snRNA-seq for the characterization of cellular diversity in the adipose tissue.

Vascular smooth muscle-derived Trpv1+ progenitors are a source of cold-induced thermogenic adipocytes.

Brown adipose tissue (BAT) and beige fat function in energy expenditure in part due to their role in thermoregulation, making these tissues attractive targets for treating obesity and metabolic disorders. While prolonged cold exposure promotes de novo recruitment of brown adipocytes, the exact sources of cold-induced thermogenic adipocytes are not completely understood. Here, we identify transient receptor potential cation channel subfamily V member 1 (Trpv1)+ vascular smooth muscle (VSM) cells as previously unidentified thermogenic adipocyte progenitors. Single-cell RNA sequencing analysis of interscapular brown adipose depots reveals, in addition to the previously known platelet-derived growth factor receptor (Pdgfr)α-expressing mesenchymal progenitors, a population of VSM-derived adipocyte progenitor cells (VSM-APC) expressing the temperature-sensitive cation channel Trpv1. We demonstrate that cold exposure induces the proliferation of Trpv1+ VSM-APCs and enahnces their differentiation to highly thermogenic adipocytes. Together, these findings illustrate the landscape of the thermogenic adipose niche at single-cell resolution and identify a new cellular origin for the development of brown and beige adipocytes.

Bioactive Khadi Cotton Fabric by Functional Designing and Immobilization of Nanosilver Nanogels.

The antimicrobial finishing is the most suitable alternative for designing medical textiles for biomedical applications. The present investigation aims at the preparation of skin-contacting khadi cotton fabric that would prevent microbial infection and offer excellent skin compatibility. A simple approach has been followed for the preparation of bioactive nanogels for antimicrobial finishing of the khadi cotton fabric. Bioactive nanogels were synthesized by using aloe vera (AV) as a reducing agent for silver ions in the presence of polyvinyl alcohol (PVA). PVA stabilizes the growth of silver nanoparticles, which is influenced by the variation in the reaction time and the temperature. Nanogels were characterized by transmission electron microscopy and scanning electron microscopy analyses. The nanogels exhibited strong antimicrobial behavior against both Staphylococcus aureus and Escherichia coli, as confirmed by the colony count method. Almost 100% antibacterial behavior was observed for the nanosilver content of 10 mM. The nanogel-finished khadi fabric showed bactericidal properties against both S. aureus and E. coli. The nanogel-finished fabric exhibited high hydrophilicity allowing complete water droplet penetration within 10 s as compared to 136 s in virgin fabric. Moreover, the skin irritation study of the fabric on male Swiss albino mice did not show any appearance of dermal toxicity. These results demonstrated that the bioactive finished khadi fabric is appropriate as skin contacting material in human health care.

µCB-seq: microfluidic cell barcoding and sequencing for high-resolution imaging and sequencing of single cells.

Single-cell RNA sequencing (scRNA-seq) enables the investigation of complex biological processes in multicellular organisms with high resolution. However, many phenotypic features that are critical to understanding the functional role of cells in a heterogeneous tissue or organ are not directly encoded in the genome and therefore cannot be profiled with scRNA-seq. Quantitative optical microscopy has long been a powerful approach for characterizing diverse cellular phenotypes including cell morphology, protein localization, and chemical composition. Combining scRNA-seq with optical imaging has the potential to provide comprehensive single-cell analysis, allowing for functional integration of gene expression profiling and cell-state characterization. However, it is difficult to track single cells through both measurements; therefore, coupling current scRNA-seq protocols with optical measurements remains a challenge. Here, we report microfluidic cell barcoding and sequencing (µCB-seq), a microfluidic platform that combines high-resolution imaging and sequencing of single cells. µCB-seq is enabled by a novel fabrication method that preloads primers with known barcode sequences inside addressable reaction chambers of a microfluidic device. In addition to enabling multi-modal single-cell analysis, µCB-seq improves gene detection sensitivity, providing a scalable and accurate method for information-rich characterization of single cells.

Cuff-Less Blood Pressure Monitoring with a 3-Axis Accelerometer.

OBJECTIVE: The aim was to propose a cuff-less, cost-efficient, and ultra-convenient blood pressure monitoring technique with a 3-axis accelerometer. METHODS: The efficacy of the proposed approach was examined in 8 young healthy volunteers undergoing different activities with a 3-axis accelerometer leveled on their upper chest. The 3-dimensional accelerations were exploited to select features for the calculation of systolic pressure (SP) and diastolic pressure (DP); the whole process involved signal processing, feature extraction, linear multivariate regression, and leave-one-out cross validations (LOOCV). RESULTS: DP and SP could be approximated with the linear combination of the extracted features: the L2 norm of lateral acceleration for both DP and SP, state variation (defined in the proposed algorithm) of vertical acceleration for SP, and I-J interval (defined in ballistocardiogram) of vertical acceleration for DP. The correlation coefficient (r) of the estimated and the measured DP was 0.97, and for SP, r = 0.96. In LOOCV, our best validated results in difference errors were -0.02±3.82 mmHg for DP and -0.59 ± 7.46 mmHg for SP. CONCLUSION: Compared to AAMI criteria, the proposed acceleration-based technique fulfilled the requirement. The accelerometer-based technique showed the potential to monitor blood pressure cuff-lessly, cost-efficiently, ultra-conveniently, and to be embedded in a long-term wearable device for clinical usage.

Quantitative imaging of lipid droplets in single cells.

The combination of next generation sequencing (NGS) and automated liquid handling platforms has led to a revolution in single-cell genomic studies. However, many molecules that are critical to understanding the functional roles of cells in a complex tissue or organs, are not directly encoded in the genome, and therefore cannot be profiled with NGS. Lipids, for example, play a critical role in many metabolic processes but cannot be detected by sequencing. Recent developments in quantitative imaging, particularly coherent Raman scattering (CRS) techniques, have produced a suite of tools for studying lipid content in single cells. This article reviews CRS imaging and computational image processing techniques for non-destructive profiling of dynamic changes in lipid composition and spatial distribution at the single-cell level. As quantitative CRS imaging progresses synergistically with microfluidic and microscopic platforms for single-cell genomic analysis, we anticipate that these techniques will bring researchers closer towards combined lipidomic and genomic analysis.