Gunsagar Gulati

Index Switching Causes “Spreading-Of-Signal” Among Multiplexed Samples In Illumina HiSeq 4000 DNA Sequencing

Illumina-based next generation sequencing (NGS) has accelerated biomedical discovery through its ability to generate thousands of gigabases of sequencing output per run at a fraction of the time and cost of conventional technologies. The process typically involves four basic steps: library preparation, cluster generation, sequencing, and data analysis. In 2015, a new chemistry of cluster generation was introduced in the newer Illumina machines (HiSeq 3000/4000/X Ten) called exclusion amplification (ExAmp), which was a fundamental shift from the earlier method of random cluster generation by bridge amplification on a non-patterned flow cell. The ExAmp chemistry, in conjunction with patterned flow cells containing nanowells at fixed locations, increases cluster density on the flow cell, thereby reducing the cost per run. It also increases sequence read quality, especially for longer read lengths (up to 150 base pairs). This advance has been widely adopted for genome sequencing because greater sequencing depth can be achieved for lower cost without compromising the quality of longer reads. We show that this promising chemistry is problematic, however, when multiplexing samples. We discovered that up to 5-10% of sequencing reads (or signals) are incorrectly assigned from a given sample to other samples in a multiplexed pool. We provide evidence that this “spreading-of-signals” arises from low levels of free index primers present in the pool. These index primers can prime pooled library fragments at random via complementary 3’ ends, and get extended by DNA polymerase, creating a new library molecule with a new index before binding to the patterned flow cell to generate a cluster for sequencing. This causes the resulting read from that cluster to be assigned to a different sample, causing the spread of signals within multiplexed samples. We show that low levels of free index primers persist after the most common library purification procedure recommended by Illumina, and that the amount of signal spreading among samples is proportional to the level of free index primer present in the library pool. This artifact causes homogenization and misclassification of cells in single cell RNA-seq experiments. Therefore, all data generated in this way must now be carefully re-examined to ensure that “spreading-of-signals” has not compromised data analysis and conclusions. Re-sequencing samples using an older technology that uses conventional bridge amplification for cluster generation, or improved library cleanup strategies to remove free index primers, can minimize or eliminate this signal spreading artifact.

Pharmacological rescue of diabetic skeletal stem cell niches

Local delivery of a missing growth factor to the skeletal stem cell niche restores bone healing in diabetic mice. Stem cells: The key to boosting bone healing in diabetes Among a myriad of difficulties, people with diabetes have problems with their bones; after a break, their bones do not heal well. Tevlin et al. use mice to investigate the cause and to devise a solution. In several models of diabetes, skeletal stem cells, which normally multiply to repair a bone injury, failed to do so. The high blood concentrations of TNFα in these diabetic mice inhibited a growth factor within the stem cell niche. The authors succeeded in reversing this deficit; delivery of the missing factor directly to the niche restored the expansion of stem cells after injury and normalized bone healing. Correction of the inhospitable niche environment for skeletal stem cells is a promising approach for this complication of diabetes and perhaps for other stem cell–based diseases. Diabetes mellitus (DM) is a metabolic disease frequently associated with impaired bone healing. Despite its increasing prevalence worldwide, the molecular etiology of DM-linked skeletal complications remains poorly defined. Using advanced stem cell characterization techniques, we analyzed intrinsic and extrinsic determinants of mouse skeletal stem cell (mSSC) function to identify specific mSSC niche–related abnormalities that could impair skeletal repair in diabetic (Db) mice. We discovered that high serum concentrations of tumor necrosis factor–α directly repressed the expression of Indian hedgehog (Ihh) in mSSCs and in their downstream skeletogenic progenitors in Db mice. When hedgehog signaling was inhibited during fracture repair, injury-induced mSSC expansion was suppressed, resulting in impaired healing. We reversed this deficiency by precise delivery of purified Ihh to the fracture site via a specially formulated, slow-release hydrogel. In the presence of exogenous Ihh, the injury-induced expansion and osteogenic potential of mSSCs were restored, culminating in the rescue of Db bone healing. Our results present a feasible strategy for precise treatment of molecular aberrations in stem and progenitor cell populations to correct skeletal manifestations of systemic disease.

Skeletal Stem Cell Niche Aberrancies Underlie Impaired Fracture Healing in a Mouse Model of Type 2 Diabetes

www.PRSJournal.com 73 Figure 1. (Left) Four-year-old female with facial infiltrating lipomatosis (FIL). (Right) Droplet digital (ddPCR) reaction showing PIK3CA mutation in muscle from patient with FIL. Left upper quadrant represents droplets with only the mutant allele. Right upper quadrant shows droplets with mutant and wild-type alleles. Left lower quadrant illustrates droplets that do not contain any alleles. Right lower quadrant has droplets with only the wild-type allele.

Optimal timing of same-admission orthotopic heart transplantation after left ventricular assist device implantation

AIM To investigate the impact of timing of same-admission orthotopic heart transplant (OHT) after left ventricular assist device (LVAD) implantation on in-hospital mortality and post-transplant length of stay. METHODS Using data from the Nationwide Inpatient Sample from 1998 to 2011, we identified patients 18 years of age or older who underwent implantation of a LVAD and for whom the procedure date was available. We calculated in-hospital mortality for those patients who underwent OHT during the same admission as a function of time from LVAD to OHT, adjusting for age, sex, race, household income, and number of comorbid diagnoses. Finally, we analyzed the effect of time to OHT after LVAD implantation on the length of hospital stay post-transplant. RESULTS Two thousand and two hundred patients underwent implantation of a LVAD in this cohort. One hundred and sixty-four (7.5%) patients also underwent OHT during the same admission, which occurred on average 32 d (IQR 7.75-66 d) after LVAD implantation. Of patients who underwent OHT, patients who underwent transplantation within 7 d of LVAD implantation (“early”) experienced increased in-hospital mortality (26.8% vs 12.2%, P = 0.0483) compared to patients who underwent transplant after 8 d (“late”). There was no statistically significant difference in age, sex, race, household income, or number of comorbid diagnoses between the early and late groups. Post-transplant length of stay after LVAD implantation was also not significantly different between patients who underwent early vs late OHT. CONCLUSION In this cohort of patients who received LVADs, the rate of in-hospital mortality after OHT was lower for patients who underwent late OHT (at least 8 d after LVAD implantation) compared to patients who underwent early OHT. Delayed timing of OHT after LVAD implantation did not correlate with longer hospital stays post-transplant.

Developmental heterogeneity of microglia and brain myeloid cells revealed by deep single-cell RNA sequencing

Microglia are increasingly recognized for their major contributions during brain development and neurodegenerative disease. It is currently unknown if these functions are carried out by subsets of microglia during different stages of development and adulthood or within specific brain regions. Here, we performed deep single-cell RNA sequencing (scRNA-seq) of microglia and related myeloid cells sorted from various regions of embryonic, postnatal, and adult mouse brains. We found that the majority of adult microglia with homeostatic signatures are remarkably similar in transcriptomes, regardless of brain region. By contrast, postnatal microglia represent a more heterogeneous population. We discovered that postnatal white matter-associated microglia (WAM) are strikingly different from microglia in other regions and express genes enriched in degenerative disease-associated microglia. These postnatal WAM have distinct amoeboid morphology, are metabolically active, and phagocytose newly formed oligodendrocytes. This scRNA-seq atlas will be a valuable resource for dissecting innate immune functions in health and disease. Highlights Myeloid scRNA-seq atlas across brain regions and developmental stages Limited transcriptomic heterogeneity of homeostatic microglia in the adult brain Phase-specific gene sets of proliferating microglia along cell cycle pseudotime Phagocytic postnatal white matter-associated microglia sharing DAM gene signatures

Isolation and functional assessment of mouse skeletal stem cell lineage

There are limited methods available to study skeletal stem, progenitor, and progeny cell activity in normal and diseased contexts. Most protocols for skeletal stem cell isolation are based on the extent to which cells adhere to plastic or whether they express a limited repertoire of surface markers. Here, we describe a flow cytometry-based approach that does not require in vitro selection and that uses eight surface markers to distinguish and isolate mouse skeletal stem cells (mSSCs); bone, cartilage, and stromal progenitors (mBCSPs); and five downstream differentiated subtypes, including chondroprogenitors, two types of osteoprogenitors, and two types of hematopoiesis-supportive stroma. We provide instructions for the optimal mechanical and chemical digestion of bone and bone marrow, as well as the subsequent flow-cytometry-activated cell sorting (FACS) gating schemes required to maximally yield viable skeletal-lineage cells. We also describe a methodology for renal subcapsular transplantation and in vitro colony-formation assays on the isolated mSSCs. The isolation of mSSCs can be completed in 9 h, with at least 1 h more required for transplantation. Experience with flow cytometry and mouse surgical procedures is recommended before attempting the protocol. Our system has wide applications and has already been used to study skeletal response to fracture, diabetes, and osteoarthritis, as well as hematopoietic stem cell-niche interactions in the bone marrow.

Incidence of temporary mechanical circulatory support before heart transplantation and impact on post-transplant outcomes

BACKGROUND Proposed changes to the United Network for Organ Sharing heart transplant allocation protocol will prioritize patients receiving temporary mechanical circulatory support (tMCS), including extracorporeal membrane oxygenation (ECMO), percutaneous ventricular assist devices (PVADs), and intra-aortic balloon pumps (IABPs). We sought to evaluate contemporary trends in the incidence and outcomes of patients who required tMCS during the hospitalization before heart transplantation. METHODS Using the National Inpatient Sample from 1998 to 2014, we identified 6,892 patients who received an orthotopic heart transplant and classified them by pre-transplant ECMO, PVAD, or IABP placement or no pre-transplant tMCS. We compared baseline characteristics and in-hospital outcomes between patients who underwent pre-transplant ECMO, PVAD, or IABP and patients who did not receive tMCS before heart transplantation. RESULTS Of patients who underwent heart transplantation, 456 (6.6%) received tMCS before transplant. During the study period, the use of tMCS more than doubled, from 17 cases per year from 1998 to 2002 to 40 cases per year from 2012 to 2014 (p < 0.001 for trend). Of patients with tMCS, 341 (74.8%) were supported by IABP, 130 (28.5%) were supported by ECMO, and 21 (4.6%) were supported by PVAD. Before 2007, patients who required tMCS had higher in-hospital mortality than patients who did not require tMCS before transplant (14.3% vs 7.5%, p = 0.05). In the subsequent era (2007 to 2014), mortality was not significantly different (4.7% vs 5.1%, p = 0.9). Hospital mortality improved over time for all patients but most significantly in patients who required tMCS (9.6% absolute risk reduction). However, patients who received tMCS had increased lengths of stays and rates of acute renal, hepatic, and respiratory failure, sepsis, bleeding complications, and surgical reoperations. CONCLUSIONS The use of tMCS before cardiac transplantation is increasing, with no difference in in-patient post-transplant mortality in the recent era between patients who did and did not receive tMCS but with increased complication rates among those who received tMCS. These data support the use of tMCS before cardiac transplantation in appropriately selected patients. Clinicians should balance the above outcomes when making decisions to implant tMCS, given the impending changes to the United Network for Organ Sharing heart allocation protocol.