Design and implementation of a biomolecular concentration tracker

As a field, synthetic biology strives to engineer increasingly complex artificial systems in living cells. Active feedback in closed loop systems offers a dynamic and adaptive way to ensure constant relative activity independent of intrinsic and extrinsic noise. In this work, we use synthetic protein scaffolds as a modular and tunable mechanism for concentration tracking through negative feedback. Input to the circuit initiates scaffold production, leading to colocalization of a two-component system and resulting in the production of an inhibitory antiscaffold protein. Using a combination of modeling and experimental work, we show that the biomolecular concentration tracker circuit achieves dynamic protein concentration tracking in Escherichia coli and that steady state outputs can be tuned

Impact of the COVID-19 global pandemic on symptomatic diagnosis of cancer - the view from primary care

The entire landscape of cancer management in primary care, from case identification to the management of those living with and beyond cancer, is evolving rapidly in the face of the coronavirus (COVID-19) pandemic.1 In a climate of fear and mandated avoidance of all but essential clinical services, delays in patient, population and healthcare system responses to suspected cancer symptoms seem inevitable

Comprehensive epigenetic landscape of rheumatoid arthritis fibroblast-like synoviocytes.

Epigenetics contributes to the pathogenesis of immune-mediated diseases like rheumatoid arthritis (RA). Here we show the first comprehensive epigenomic characterization of RA fibroblast-like synoviocytes (FLS), including histone modifications (H3K27ac, H3K4me1, H3K4me3, H3K36me3, H3K27me3, and H3K9me3), open chromatin, RNA expression and whole-genome DNA methylation. To address complex multidimensional relationship and reveal epigenetic regulation of RA, we perform integrative analyses using a novel unbiased method to identify genomic regions with similar profiles. Epigenomically similar regions exist in RA cells and are associated with active enhancers and promoters and specific transcription factor binding motifs. Differentially marked genes are enriched for immunological and unexpected pathways, with "Huntington's Disease Signaling" identified as particularly prominent. We validate the relevance of this pathway to RA by showing that Huntingtin-interacting protein-1 regulates FLS invasion into matrix. This work establishes a high-resolution epigenomic landscape of RA and demonstrates the potential for integrative analyses to identify unanticipated therapeutic targets

CAV1 inhibits metastatic potential in melanomas through suppression of the Integrin/Src/FAK signaling pathway.

Caveolin-1 (CAV1) is the main structural component of Caveolae which are plasma membrane invaginations that participate in vesicular trafficking and signal transduction events. Although, evidence has recently accumulated describing the function of CAV1 in several cancer types, its role in melanoma tumor formation and progression remains poorly explored. Here, by employing B16F10 melanoma cells as an experimental system, we directly explore the function of CAV1 in melanoma tumor growth and metastasis. We first show that CAV1 expression promotes proliferation while it suppresses migration and invasion of B16F10 cells in vitro. When orthotopically implanted in the skin of mice, B16F10 cells expressing CAV1 form tumors that are similar in size to their control counterpart. An experimental metastasis assay demonstrates that CAV1 expression suppresses the ability of B16F10 cells to form lung metastases in C57Bl/6 syngeneic mice. Additionally, CAV1 protein and mRNA levels are found to be significantly reduced in human metastatic melanoma cell lines and human tissue from metastatic lesions. Finally, we demonstrate that following integrin activation, B16F10 cells expressing CAV1 display reduced expression levels and activity of FAK and Src proteins. CAV1 expression also markedly reduces the expression levels of beta3 Integrin in B16F10 melanoma cells. In summary, our findings provide experimental evidence that CAV1 may function as an antimetastatic gene in malignant melanoma

Metabolic remodeling of the tumor microenvironment: migration stimulating factor (MSF) reprograms myofibroblasts toward lactate production, fueling anabolic tumor growth.

Migration stimulating factor (MSF) is a genetically truncated N-terminal isoform of fibronectin that is highly expressed during mammalian development in fetal fibroblasts, and during tumor formation in human cancer-associated myofibroblasts. However, its potential functional role in regulating tumor metabolism remains unexplored. Here, we generated an immortalized fibroblast cell line that recombinantly overexpresses MSF and studied their properties relative to vector-alone control fibroblasts. Our results indicate that overexpression of MSF is sufficient to confer myofibroblastic differentiation, likely via increased TGF-b signaling. In addition, MSF activates the inflammation-associated transcription factor NFκB, resulting in the onset of autophagy/mitophagy, thereby driving glycolytic metabolism (L-lactate production) in the tumor microenvironment. Consistent with the idea that glycolytic fibroblasts fuel tumor growth (via L-lactate, a high-energy mitochondrial fuel), MSF fibroblasts significantly increased tumor growth, by up to 4-fold. Mechanistic dissection of the MSF signaling pathway indicated that Cdc42 lies downstream of MSF and fibroblast activation. In accordance with this notion, Cdc42 overexpression in immortalized fibroblasts was sufficient to drive myofibroblast differentiation, to provoke a shift towards glycolytic metabolism and to promote tumor growth by up to 2-fold. In conclusion, the MSF/Cdc42/NFκB signaling cascade may be a critical druggable target in preventing Warburg-like cancer metabolism in tumor-associated fibroblasts. Thus, MSF functions in the metabolic remodeling of the tumor microenvironment by metabolically reprogramming cancer-associated fibroblasts toward glycolytic metabolism

Design and implementation of a synthetic biomolecular concentration tracker

As a field, synthetic biology strives to engineer increasingly complex artificial systems in living cells. Active feedback in closed loop systems offers a dynamic and adaptive way to ensure constant relative activity independent of intrinsic and extrinsic noise. In this work, we use synthetic protein scaffolds as a modular and tunable mechanism for concentration tracking through negative feedback. Input to the circuit initiates scaffold production, leading to colocalization of a two-component system and resulting in the production of an inhibitory antiscaffold protein. Using a combination of modeling and experimental work, we show that the biomolecular concentration tracker circuit achieves dynamic protein concentration tracking in Escherichia coli and that steady state outputs can be tuned

Quantifying the Effects of Known Unknowns on Inferred High-redshift Galaxy Properties: Burstiness, the IMF, and Nebular Physics

The era of the James Webb Space Telescope ushers stellar populations models into uncharted territories, particularly at the high-redshift frontier. In a companion paper, we apply the \texttt{Prospector} Bayesian framework to jointly infer galaxy redshifts and stellar populations properties from broad-band photometry as part of the UNCOVER survey. Here we present a comprehensive error budget in spectral energy distribution (SED) modeling. Using a $z_{\rm phot}>9$ sample, we quantify the systematic shifts stemming from various model choices in inferred stellar mass, star formation rate (SFR), and age. These choices encompass different timescales for changes in the star formation history (SFH), non-universal stellar initial mass functions (IMF), and the inclusion of variable nebular abundances, gas density and ionizing photon budget. We find that the IMF exerts the strongest influence on the inferred properties: the systematic uncertainties can be as much as 1 dex, 2--5 times larger than the formal reported uncertainties in mass and SFR; and importantly, exceed the scatter seen when using different SED fitting codes. This means that a common practice in the literature of assessing uncertainties in SED-fitting processes by comparing multiple codes is substantively underestimating the true systematic uncertainty. Highly stochastic SFHs change the inferred SFH by much larger than the formal uncertainties, and introduce $\sim 0.8$ dex systematics in SFR and $\sim 0.3$ dex systematics in average age. Finally, employing a flexible nebular emission model causes $\sim 0.2$ dex systematic increase in mass, comparable to the formal uncertainty. This paper constitutes one of the initial steps toward a complete uncertainty estimate in SED modeling.Comment: Submitted to ApJ. 18 pages, 8 figures, 2 table

The International Surface Pressure Databank version 2

The International Surface Pressure Databank (ISPD) is the world's largest collection of global surface and sea-level pressure observations. It was developed by extracting observations from established international archives, through international cooperation with data recovery facilitated by the Atmospheric Circulation Reconstructions over the Earth (ACRE) initiative, and directly by contributing universities, organizations, and countries. The dataset period is currently 1768–2012 and consists of three data components: observations from land stations, marine observing systems, and tropical cyclone best track pressure reports. Version 2 of the ISPD (ISPDv2) was created to be observational input for the Twentieth Century Reanalysis Project (20CR) and contains the quality control and assimilation feedback metadata from the 20CR. Since then, it has been used for various general climate and weather studies, and an updated version 3 (ISPDv3) has been used in the ERA-20C reanalysis in connection with the European Reanalysis of Global Climate Observations project (ERA-CLIM). The focus of this paper is on the ISPDv2 and the inclusion of the 20CR feedback metadata. The Research Data Archive at the National Center for Atmospheric Research provides data collection and access for the ISPDv2, and will provide access to future versions

Body mass index and height over three generations: evidence from the Lifeways cross-generational cohort study

Background: Obesity and its measure of body mass index are strongly determined by parental body size. Debate continues as to whether both parents contribute equally to offspring body mass which is key to understanding the aetiology of the disease. The aim of this study was to use cohort data from three generations of one family to examine the relative maternal and paternal associations with offspring body mass index and how these associations compare with family height to demonstrate evidence of genetic or environmental cross-generational transmission. Methods: 669 of 1082 families were followed up in 2007/8 as part of the Lifeways study, a prospective observational cross-generation linkage cohort. Height and weight were measured in 529 Irish children aged 5 to 7 years and were self-reported by parents and grandparents. All adults provided information on self-rated health, education status, and indicators of income, diet and physical activity. Associations between the weight, height, and body mass index of family members were examined with mixed models and heritability estimates computed using linear regression analysis. Results: Self-rated health was associated with lower BMI for all family members, as was age for children. When these effects were accounted for evidence of familial associations of BMI from one generation to the next was more apparent in the maternal line. Heritability estimates were higher (h2 = 0.40) for mother-offspring pairs compared to father-offspring pairs (h2 = 0.22). In the previous generation, estimates were higher between mothersparents (h2 = 0.54-0.60) but not between fathers-parents (h2 = -0.04-0.17). Correlations between mother and offspring across two generations remained significant when modelled with fixed variables of socioeconomic status, health, and lifestyle. A similar analysis of height showed strong familial associations from maternal and paternal lines across each generation. Conclusions: This is the first family cohort study to report an enduring association between mother and offspring BMI over three generations. The evidence of BMI transmission over three generations through the maternal line in an observational study corroborates the findings of animal studies. A more detailed analysis of geno and phenotypic data over three generations is warranted to understand the nature of this maternal-offspring relationship.TS 24.4.1