Peter A. Sims

Gremlin 1 Identifies a Skeletal Stem Cell with Bone, Cartilage, and Reticular Stromal Potential

The stem cells that maintain and repair the postnatal skeleton remain undefined. One model suggests that perisinusoidal mesenchymal stem cells (MSCs) give rise to osteoblasts, chondrocytes, marrow stromal cells, and adipocytes, although the existence of these cells has not been proven through fate-mapping experiments. We demonstrate here that expression of the bone morphogenetic protein (BMP) antagonist gremlin 1 defines a population of osteochondroreticular (OCR) stem cells in the bone marrow. OCR stem cells self-renew and generate osteoblasts, chondrocytes, and reticular marrow stromal cells, but not adipocytes. OCR stem cells are concentrated within the metaphysis of long bones not in the perisinusoidal space and are needed for bone development, bone remodeling, and fracture repair. Grem1 expression also identifies intestinal reticular stem cells (iRSCs) that are cells of origin for the periepithelial intestinal mesenchymal sheath. Grem1 expression identifies distinct connective tissue stem cells in both the bone (OCR stem cells) and the intestine (iRSCs).

Digital RNA sequencing minimizes sequence-dependent bias and amplification noise with optimized single-molecule barcodes.

RNA sequencing (RNA-Seq) is a powerful tool for transcriptome profiling, but is hampered by sequence-dependent bias and inaccuracy at low copy numbers intrinsic to exponential PCR amplification. We developed a simple strategy for mitigating these complications, allowing truly digital RNA-Seq. Following reverse transcription, a large set of barcode sequences is added in excess, and nearly every cDNA molecule is uniquely labeled by random attachment of barcode sequences to both ends. After PCR, we applied paired-end deep sequencing to read the two barcodes and cDNA sequences. Rather than counting the number of reads, RNA abundance is measured based on the number of unique barcode sequences observed for a given cDNA sequence. We optimized the barcodes to be unambiguously identifiable, even in the presence of multiple sequencing errors. This method allows counting with single-copy resolution despite sequence-dependent bias and PCR-amplification noise, and is analogous to digital PCR but amendable to quantifying a whole transcriptome. We demonstrated transcriptome profiling of Escherichia coli with more accurate and reproducible quantification than conventional RNA-Seq.

Organelle tracking in a living cell with microsecond time resolution and nanometer spatial precision

The study of cellular processes such as organelle transport often demands particle tracking with microsecond time-resolution and nanometer spatial precision, posing significant challenges to existing tracking methods. Here, we have developed a novel strategy for two-dimensional tracking of gold nanoparticles (GNPs) with 25 mus time resolution and approximately 1.5 nm spatial precision, by using a quadrant photodiode to record the positions of GNPs in an objective-type dark-field microscope. In combination with a feedback loop, this technique records long, high time-resolution and spatial precision trajectories of endocytosed GNPs transported by the molecular motors kinesin and dynein in a living cell. In the full range of organelle velocities (0-8 microm s(-1)), we clearly resolve the individual 8 nm steps of cargoes carried by kinesin, and the 8, 12, 16, 20, and 24 nm steps of those carried by dynein. These experiments yield new information about molecular motor stepping in living cells.

MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma.

Significance Molecular analysis of surgically resected glioblastomas (GBM) samples has uncovered phenotypically and clinically distinct tumor subtypes. However, little is known about the molecular features of the glioma margins that are left behind after surgery. To address this key issue, we performed RNA-sequencing (RNA-seq) and histological analysis on MRI-guided biopsies from the contrast-enhancing core and nonenhancing margins of GBM. Computational deconvolution of the RNA-seq data revealed that cellular composition, including nonneoplastic cells, is a major determinant of the expression patterns at the margins of GBM. The different GBM subtypes show distinct expression patterns that relate the contrast enhancing centers to the nonenhancing margins of tumors. Understanding these patterns may provide a means to infer the molecular and cellular features of residual disease. Glioblastomas (GBMs) diffusely infiltrate the brain, making complete removal by surgical resection impossible. The mixture of neoplastic and nonneoplastic cells that remain after surgery form the biological context for adjuvant therapeutic intervention and recurrence. We performed RNA-sequencing (RNA-seq) and histological analysis on radiographically guided biopsies taken from different regions of GBM and showed that the tissue contained within the contrast-enhancing (CE) core of tumors have different cellular and molecular compositions compared with tissue from the nonenhancing (NE) margins of tumors. Comparisons with the The Cancer Genome Atlas dataset showed that the samples from CE regions resembled the proneural, classical, or mesenchymal subtypes of GBM, whereas the samples from the NE regions predominantly resembled the neural subtype. Computational deconvolution of the RNA-seq data revealed that contributions from nonneoplastic brain cells significantly influence the expression pattern in the NE samples. Gene ontology analysis showed that the cell type-specific expression patterns were functionally distinct and highly enriched in genes associated with the corresponding cell phenotypes. Comparing the RNA-seq data from the GBM samples to that of nonneoplastic brain revealed that the differentially expressed genes are distributed across multiple cell types. Notably, the patterns of cell type-specific alterations varied between the different GBM subtypes: the NE regions of proneural tumors were enriched in oligodendrocyte progenitor genes, whereas the NE regions of mesenchymal GBM were enriched in astrocytic and microglial genes. These subtype-specific patterns provide new insights into molecular and cellular composition of the infiltrative margins of GBM.

Probing Dynein and Kinesin Stepping with Mechanical Manipulation in a Living Cell

We report a label-free assay for simultaneous optical manipulation and tracking of endogenous lipid droplets as actively transported cargoes in a living mammalian cell with sub-millisecond time resolution. Using an EM-CCD camera as a highly sensitive quadrant detector, we can detect steps of dynein- and kinesin-driven cargoes under known force loads. We can distinguish single and multiple motor-driven cargoes and show that the stall forces for inward and outward transported cargoes are similar. By combining the stall force observable with the ability to detect individual steps, we can characterize kinesin- and dynein-driven active transport in different force regimes.

Scalable microfluidics for single-cell RNA printing and sequencing.

Many important biological questions demand single-cell transcriptomics on a large scale. Hence, new tools are urgently needed for efficient, inexpensive manipulation of RNA from individual cells. We report a simple platform for trapping single-cell lysates in sealed, picoliter microwells capable of printing RNA on glass or capturing RNA on beads. We then develop a scalable technology for genome-wide, single-cell RNA-Seq. Our device generates pooled libraries from hundreds of individual cells with consumable costs of

Digital Polymerase Chain Reaction in an Array of Femtoliter Polydimethylsiloxane Microreactors

0.10–

Ribosome Profiling Reveals a Cell-Type-Specific Translational Landscape in Brain Tumors

0.20 per cell and includes five lanes for simultaneous experiments. We anticipate that this system will serve as a general platform for single-cell imaging and sequencing.

Patterns of Gene-Specific and Total Transcriptional Activity during the Plasmodium falciparum Intraerythrocytic Developmental Cycle

We developed a simple, compact microfluidic device to perform high dynamic-range digital polymerase chain reaction (dPCR) in an array of isolated 36-femtoliter microreactors. The density of the microreactors exceeded 20000/mm(2). This device, made from polydimethylsiloxane (PDMS), allows the samples to be loaded into all microreactors simultaneously. The microreactors are completely sealed through the deformation of a PDMS membrane. The small volume of the microreactors ensures a compact device with high reaction efficiency and low reagent and sample consumption. Future potential applications of this platform include multicolor dPCR and massively parallel dPCR for next generation sequencing library preparation.

An Automated Microwell Platform for Large-Scale Single Cell RNA-Seq

Glioma growth is driven by signaling that ultimately regulates protein synthesis. Gliomas are also complex at the cellular level and involve multiple cell types, including transformed and reactive cells in the brain tumor microenvironment. The distinct functions of the various cell types likely lead to different requirements and regulatory paradigms for protein synthesis. Proneural gliomas can arise from transformation of glial progenitors that are driven to proliferate via mitogenic signaling that affects translation. To investigate translational regulation in this system, we developed a RiboTag glioma mouse model that enables cell-type-specific, genome-wide ribosome profiling of tumor tissue. Infecting glial progenitors with Cre-recombinant retrovirus simultaneously activates expression of tagged ribosomes and delivers a tumor-initiating mutation. Remarkably, we find that although genes specific to transformed cells are highly translated, their translation efficiencies are low compared with normal brain. Ribosome positioning reveals sequence-dependent regulation of ribosomal activity in 5′-leaders upstream of annotated start codons, leading to differential translation in glioma compared with normal brain. Additionally, although transformed cells express a proneural signature, untransformed tumor-associated cells, including reactive astrocytes and microglia, express a mesenchymal signature. Finally, we observe the same phenomena in human disease by combining ribosome profiling of human proneural tumor and non-neoplastic brain tissue with computational deconvolution to assess cell-type-specific translational regulation.