PERT: A Method for Expression Deconvolution of Human Blood Samples from Varied Microenvironmental and Developmental Conditions

The cellular composition of heterogeneous samples can be predicted using an expression deconvolution algorithm to decompose their gene expression profiles based on pre-defined, reference gene expression profiles of the constituent populations in these samples. However, the expression profiles of the actual constituent populations are often perturbed from those of the reference profiles due to gene expression changes in cells associated with microenvironmental or developmental effects. Existing deconvolution algorithms do not account for these changes and give incorrect results when benchmarked against those measured by well-established flow cytometry, even after batch correction was applied. We introduce PERT, a new probabilistic expression deconvolution method that detects and accounts for a shared, multiplicative perturbation in the reference profiles when performing expression deconvolution. We applied PERT and three other state-of-the-art expression deconvolution methods to predict cell frequencies within heterogeneous human blood samples that were collected under several conditions (uncultured mono-nucleated and lineage-depleted cells, and culture-derived lineage-depleted cells). Only PERT's predicted proportions of the constituent populations matched those assigned by flow cytometry. Genes associated with cell cycle processes were highly enriched among those with the largest predicted expression changes between the cultured and uncultured conditions. We anticipate that PERT will be widely applicable to expression deconvolution strategies that use profiles from reference populations that vary from the corresponding constituent populations in cellular state but not cellular phenotypic identity

The Effect of Sugar-Free Versus Sugar-Sweetened Beverages on Satiety, Liking and Wanting: An 18 Month Randomized Double-Blind Trial in Children

BACKGROUND: Substituting sugar-free for sugar-sweetened beverages reduces weight gain. A possible explanation is that sugar-containing and sugar-free beverages cause the same degree of satiety. However, this has not been tested in long-term trials. METHODS: We randomized 203 children aged 7-11 years to receive 250 mL per day of an artificially sweetened sugar-free beverage or a similarly looking and tasting sugar-sweetened beverage. We measured satiety on a 5-point scale by questionnaire at 0, 6, 12 and 18 months. We calculated the change in satiety from before intake to 1 minute after intake and 15 minutes after intake. We then calculated the odds ratio that satiety increased by 1 point in the sugar-group versus the sugar-free group. We also investigated how much the children liked and wanted the beverages. RESULTS: 146 children or 72% completed the study. We found no statistically significant difference in satiety between the sugar-free and sugar-sweetened group; the adjusted odds ratio for a 1 point increase in satiety in the sugar group versus the sugar-free group was 0.77 at 1 minute (95% confidence interval, 0.46 to 1.29), and 1.44 at 15 minutes after intake (95% CI, 0.86 to 2.40). The sugar-group liked and wanted their beverage slightly more than the sugar-free group, adjusted odds ratio 1.63 (95% CI 1.05 to 2.54) and 1.65 (95% CI 1.07 to 2.55), respectively. CONCLUSIONS: Sugar-sweetened and sugar-free beverages produced similar satiety. Therefore when children are given sugar-free instead of sugar-containing drinks they might not make up the missing calories from other sources. This may explain our previous observation that children in the sugar-free group accumulated less body fat than those in the sugar group.<br /

CXCL12 and [N33A]CXCL12 in 5637 and HeLa Cells: Regulating HER1 Phosphorylation via Calmodulin/Calcineurin

In the human neoplastic cell lines 5637 and HeLa, recombinant CXCL12 elicited, as expected, downstream signals via both G-protein-dependent and β-arrestin-dependent pathways responsible for inducing a rapid and a late wave, respectively, of ERK1/2 phosphorylation. In contrast, the structural variant [N33A]CXCL12 triggered no β-arrestin-dependent phosphorylation of ERK1/2, and signaled via G protein-dependent pathways alone. Both CXCL12 and [N33A]CXCL12, however, generated signals that transinhibited HER1 phosphorylation via intracellular pathways. 1) Prestimulation of CXCR4/HER1-positive 5637 or HeLa cells with CXCL12 modified the HB-EGF-dependent activation of HER1 by delaying the peak phosphorylation of tyrosine 1068 or 1173. 2) Prestimulation with the synthetic variant [N33A]CXCL12, while preserving CXCR4-related chemotaxis and CXCR4 internalization, abolished HER1 phosphorylation. 3) In cells knockdown of β-arrestin 2, CXCL12 induced a full inhibition of HER1 like [N33A]CXCL12 in non-silenced cells. 4) HER1 phosphorylation was restored as usual by inhibiting PCK, calmodulin or calcineurin, whereas the inhibition of CaMKII had no discernable effect. We conclude that both recombinant CXCL12 and its structural variant [N33A]CXCL12 may transinhibit HER1 via G-proteins/calmodulin/calcineurin, but [N33A]CXCL12 does not activate β-arrestin-dependent ERK1/2 phosphorylation and retains a stronger inhibitory effect. Therefore, we demonstrated that CXCL12 may influence the magnitude and the persistence of signaling downstream of HER1 in turn involved in the proliferative potential of numerous epithelial cancer. In addition, we recognized that [N33A]CXCL12 activates preferentially G-protein-dependent pathways and is an inhibitor of HER1

Microfluidic Perfusion for Regulating Diffusible Signaling in Stem Cells

Background Autocrine & paracrine signaling are widespread both in vivo and in vitro, and are particularly important in embryonic stem cell (ESC) pluripotency and lineage commitment. Although autocrine signaling via fibroblast growth factor-4 (FGF4) is known to be required in mouse ESC (mESC) neuroectodermal specification, the question of whether FGF4 autocrine signaling is sufficient, or whether other soluble ligands are also involved in fate specification, is unknown. The spatially confined and closed-loop nature of diffusible signaling makes its experimental control challenging; current experimental approaches typically require prior knowledge of the factor/receptor in order to modulate the loop. A new approach explored in this work is to leverage transport phenomena at cellular resolution to downregulate overall diffusible signaling through the physical removal of cell-secreted ligands. Methodology/Principal Findings We develop a multiplex microfluidic platform to continuously remove cell-secreted (autocrine\paracrine) factors to downregulate diffusible signaling. By comparing cell growth and differentiation in side-by-side chambers with or without added cell-secreted factors, we isolate the effects of diffusible signaling from artifacts such as shear, nutrient depletion, and microsystem effects, and find that cell-secreted growth factor(s) are required during neuroectodermal specification. Then we induce FGF4 signaling in minimal chemically defined medium (N2B27) and inhibit FGF signaling in fully supplemented differentiation medium with cell-secreted factors to determine that the non-FGF cell-secreted factors are required to promote growth of differentiating mESCs. Conclusions/Significance Our results demonstrate for the first time that flow can downregulate autocrine\paracrine signaling and examine sufficiency of extracellular factors. We show that autocrine\paracrine signaling drives neuroectodermal commitment of mESCs through both FGF4-dependent and -independent pathways. Overall, by uncovering autocrine\paracrine processes previously hidden in conventional culture systems, our results establish microfluidic perfusion as a technique to study and manipulate diffusible signaling in cell systems.National Institutes of Health (U.S.) (NIH grant No. EB007278)Swiss National Science FoundationSwiss National Science Foundatio

Identifying Extrinsic versus Intrinsic Drivers of Variation in Cell Behavior in Human iPSC Lines from Healthy Donors

Large cohorts of human induced pluripotent stem cells (iPSCs) from healthy donors are a potentially powerful tool for investigating the relationship between genetic variants and cellular behavior. Here, we integrate high content imaging of cell shape, proliferation, and other phenotypes with gene expression and DNA sequence datasets from over 100 human iPSC lines. By applying a dimensionality reduction approach, Probabilistic Estimation of Expression Residuals (PEER), we extracted factors that captured the effects of intrinsic (genetic concordance between different cell lines from the same donor) and extrinsic (cell responses to different fibronectin concentrations) conditions. We identify genes that correlate in expression with intrinsic and extrinsic PEER factors and associate outlier cell behavior with genes containing rare deleterious non-synonymous SNVs. Our study, thus, establishes a strategy for examining the genetic basis of inter-individual variability in cell behavior

A multi-platform approach to identify a blood-based host protein signature for distinguishing between bacterial and viral infections in febrile children (PERFORM): a multi-cohort machine learning study

BACKGROUND: Differentiating between self-resolving viral infections and bacterial infections in children who are febrile is a common challenge, causing difficulties in identifying which individuals require antibiotics. Studying the host response to infection can provide useful insights and can lead to the identification of biomarkers of infection with diagnostic potential. This study aimed to identify host protein biomarkers for future development into an accurate, rapid point-of-care test that can distinguish between bacterial and viral infections, by recruiting children presenting to health-care settings with fever or a history of fever in the previous 72 h. METHODS: In this multi-cohort machine learning study, patient data were taken from EUCLIDS, the Swiss Pediatric Sepsis study, the GENDRES study, and the PERFORM study, which were all based in Europe. We generated three high-dimensional proteomic datasets (SomaScan and two via liquid chromatography tandem mass spectrometry, referred to as MS-A and MS-B) using targeted and untargeted platforms (SomaScan and liquid chromatography mass spectrometry). Protein biomarkers were then shortlisted using differential abundance analysis, feature selection using forward selection-partial least squares (FS-PLS; 100 iterations), along with a literature search. Identified proteins were tested with Luminex and ELISA and iterative FS-PLS was done again (25 iterations) on the Luminex results alone, and the Luminex and ELISA results together. A sparse protein signature for distinguishing between bacterial and viral infections was identified from the selected proteins. The performance of this signature was finally tested using Luminex assays and by calculating disease risk scores. FINDINGS: 376 children provided serum or plasma samples for use in the discovery of protein biomarkers. 79 serum samples were collected for the generation of the SomaScan dataset, 147 plasma samples for the MS-A dataset, and 150 plasma samples for the MS-B dataset. Differential abundance analysis, and the first round of feature selection using FS-PLS identified 35 protein biomarker candidates, of which 13 had commercial ELISA or Luminex tests available. 16 proteins with ELISA or Luminex tests available were identified by literature review. Further evaluation via Luminex and ELISA and the second round of feature selection using FS-PLS revealed a six-protein signature: three of the included proteins are elevated in bacterial infections (SELE, NGAL, and IFN-γ), and three are elevated in viral infections (IL18, NCAM1, and LG3BP). Performance testing of the signature using Luminex assays revealed area under the receiver operating characteristic curve values between 89·4% and 93·6%. INTERPRETATION: This study has led to the identification of a protein signature that could be ultimately developed into a blood-based point-of-care diagnostic test for rapidly diagnosing bacterial and viral infections in febrile children. Such a test has the potential to greatly improve care of children who are febrile, ensuring that the correct individuals receive antibiotics. FUNDING: European Union's Horizon 2020 research and innovation programme, the European Union's Seventh Framework Programme (EUCLIDS), Imperial Biomedical Research Centre of the National Institute for Health Research, the Wellcome Trust and Medical Research Foundation, Instituto de Salud Carlos III, Consorcio Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Grupos de Refeencia Competitiva, Swiss State Secretariat for Education, Research and Innovation

Soft Substrates Promote Homogeneous Self-Renewal of Embryonic Stem Cells via Downregulating Cell-Matrix Tractions

Maintaining undifferentiated mouse embryonic stem cell (mESC) culture has been a major challenge as mESCs cultured in Leukemia Inhibitory Factor (LIF) conditions exhibit spontaneous differentiation, fluctuating expression of pluripotency genes, and genes of specialized cells. Here we show that, in sharp contrast to the mESCs seeded on the conventional rigid substrates, the mESCs cultured on the soft substrates that match the intrinsic stiffness of the mESCs and in the absence of exogenous LIF for 5 days, surprisingly still generated homogeneous undifferentiated colonies, maintained high levels of Oct3/4, Nanog, and Alkaline Phosphatase (AP) activities, and formed embryoid bodies and teratomas efficiently. A different line of mESCs, cultured on the soft substrates without exogenous LIF, maintained the capacity of generating homogeneous undifferentiated colonies with relatively high levels of Oct3/4 and AP activities, up to at least 15 passages, suggesting that this soft substrate approach applies to long term culture of different mESC lines. mESC colonies on these soft substrates without LIF generated low cell-matrix tractions and low stiffness. Both tractions and stiffness of the colonies increased with substrate stiffness, accompanied by downregulation of Oct3/4 expression. Our findings demonstrate that mESC self-renewal and pluripotency can be maintained homogeneously on soft substrates via the biophysical mechanism of facilitating generation of low cell-matrix tractions

Stemming Cancer: Functional Genomics of Cancer Stem Cells in Solid Tumors

Cancer stem cells (CSCs) were discovered about 15 years ago in hematopoietic cancers. Subsequently, cancer stem cells were discovered in various solid tumors. Based on parallels with normal stem cells, a developmental process of cancer stem cells follows paths of organized, hierarchical structure of cells with different degrees of maturity. While some investigators have reported particular markers as identification of cancer stem cells, these markers require further research. In this review, we focus on the functional genomics of cancer stem cells. Functional genomics provides useful information on the signaling pathways which are consecutively activated or inactivated amongst those cells. This information is of particular importance for cancer research and clinical treatment in many respects. (1) Understanding of self-renewal mechanisms crucial to tumor growth. (2) Allow the identification of new, more specific marker for CSCs, and (3) pathways that are suitable as future targets for anti-cancer drugs. This is of particular importance, because today’s chemotherapy targets the proliferating cancer cells sparing the relatively slow dividing cancer stem cells. The first step on this long road therefore is to analyze genome-wide expression-profiles within the same type of cancer and then between different types of cancer, encircling those target genes and pathways, which are specific to these cells