Does sweetness exposure drive 'sweet tooth'?

It is widely believed that exposure to sweetened foods and beverages stimulates the liking and desire for sweetness. Here we provide an updated review of the empirical evidence from human research examining whether exposure to sweet foods or beverages influences subsequent general liking for sweetness (‘sweet tooth’), based on the conclusions of existing systematic reviews and more recent research identified from a structured search of literature. Prior reviews have concluded that the evidence for a relationship between sweet taste exposure and measures of sweet taste liking is equivocal, and more recent primary research generally does not support the view that exposure drives increased liking for sweetness, in adults or children. In intervention trials using a range of designs, acute exposure to sweetness usually has the opposite effect (reducing subsequent liking and desire for sweet taste), while sustained exposures have no significant effects or inconsistent effects. Recent longitudinal observational studies in infants and children also report no significant associations between exposures to sweet foods and beverages with measures of sweet taste preferences. Overall, while it is widely assumed that exposure to sweetness stimulates a greater liking and desire for sweetness, this is not borne out by the balance of empirical evidence. While new research may provide a more robust evidence base, there are also a number of methodological, biological and behavioural considerations that may underpin the apparent absence of a positive relationship between sweetness exposure and liking.

Gastrointestinal tolerance of D-allulose in children: an acute, randomised, double-blind, placebo-controlled, cross-over study

D-Allulose, a low-calorie sugar, provides an attractive alternative to added sugars in food and beverage products. There is however limited data on its gastrointestinal (GI) tolerance, with only two studies in adults, and no studies in children to date. We therefore performed an acute, randomised, double-blind, placebo-controlled, cross over study designed to determine, for the first time, the GI tolerance of 2 doses of D-allulose (2.5 g per 120 ml and 4.3 g per 120 ml) in young children. The primary tolerance endpoint was the difference in the number of participants experiencing at least one stool that met a Type 6 or Type 7 description on the Bristol Stool Chart, within 24 hours after study product intake. Secondary endpoints included the assessment of stool frequency, stool consistency, and the presence of GI symptoms. Only one participant in the low dose group experienced a stool type 6 or 7, while no participants experienced a stool type 6 or 7 in the high dose group. A statistically significant difference in the change in stool frequency compared to placebo in the high dose group (p = 0.044) was found, with no significant difference between the groups for stool consistency and no participants experienced unusual stool frequency. All the encountered adverse events were non-serious, either mild or moderate, and there were no serious adverse events. All in all, D-allulose was tolerated well in children, making this ingredient a good candidate to reformulate commercially produced goods by replacing added sugars with lower caloric content.

Differential detection workflows for multi-sample single-cell RNA-seq data

In single-cell transcriptomics, differential gene expression (DE) analyses typically focus on testing differences in the average expression of genes between cell types or conditions of interest. Single-cell transcriptomics, however, also has the promise to prioritise genes for which the expression differ in other aspects of the distribution. Here we develop a workflow for assessing differential detection (DD), which tests for differences in the average fraction of samples or cells in which a gene is detected. After benchmarking eight different DD data analysis strategies, we provide a unified workflow for jointly assessing DE and DD. Using simulations and two case studies, we show that DE and DD analysis provide complementary information, both in terms of the individual genes they report and in the functional interpretation of those genes.

A Global Transcriptional Atlas of the Effect of Sleep Deprivation in the Mouse Frontal Cortex

Sleep deprivation (SD) has negative effects on brain function. Sleep problems are prevalent in neurodevelopmental, neurodegenerative and psychiatric disorders. Thus, understanding the molecular consequences of SD is of fundamental importance in neuroscience. In this study, we present the first simultaneous bulk and single-nuclear (sn)RNA sequencing characterization of the effects of SD in the mouse frontal cortex. We show that SD predominantly affects glutamatergic neurons, specifically in layers 4 and 5, and produces isoform switching of thousands of transcripts. At both the global and cell-type specific level, SD has a large repressive effect on transcription, down-regulating thousands of genes and transcripts; underscoring the importance of accounting for the effects of sleep loss in transcriptome studies of brain function. As a resource we provide extensive characterizations of cell types, genes, transcripts and pathways affected by SD; as well as tutorials for data analysis.

A Latent Activated Olfactory Stem Cell State Revealed by Single Cell Transcriptomic and Epigenomic Profiling

The olfactory epithelium is one of the few regions of the nervous system that sustains neurogenesis throughout life. Its experimental accessibility makes it especially tractable for studying molecular mechanisms that drive neural regeneration after injury-induced cell death. In this study, we used single cell sequencing to identify major regulatory players in determining olfactory epithelial stem cell fate after acute injury. We combined gene expression and accessible chromatin profiles of individual lineage traced olfactory stem cells to predict transcription factor activity specific to different lineages and stages of recovery. We further identified a discrete stem cell state that appears poised for activation, characterized by accessible chromatin around wound response and lineage specific genes prior to their later expression in response to injury. Together these results provide evidence that a subset of quiescent olfactory epithelial stem cells are epigenetically primed to support injury-induced regeneration.

Low-no-calorie sweeteners exert marked compound-specific impact on the human gut microbiota ex vivo

Low-no-calorie sweeteners (LNCS) are used as sugar substitutes as part of strategies to reduce the risk of chronic diseases related to high sugar intake (e.g. type 2 diabetes (T2D)). This study investigated how a range of sweeteners [tagatose (TA)/maltitol (MA)/sorbitol (SO)/stevia (ST)/sucralose (SU)/acesulfame K (ACK)] impact the gut microbiota of T2D subjects and healthy human adults using the ex vivo SIFR® technology (n = 12). The cohort covered clinically relevant interpersonal and T2D-related differences. ACK/SU remained intact while not impacting microbial composition and metabolite production. In contrast, TA/SO and ST/MA were respectively readily and gradually fermented. ST and particularly TA/SO/MA increased bacterial density and SCFA production product-specifically: SO increased acetate (∼Bifidobacterium adolescentis), whilst MA/ST increased propionate (∼Parabacteroides distasonis). TA exerted low specificity as it increased butyrate for healthy subjects, yet propionate for T2D subjects. Overall, LNCS exerted highly compound-specific effects stressing that results obtained for one LNCS cannot be generalised to other LNCS.

Curated single cell multimodal landmark datasets for R/Bioconductor

BACKGROUND

The majority of high-throughput single-cell molecular profiling methods quantify RNA expression; however, recent multimodal profiling methods add simultaneous measurement of genomic, proteomic, epigenetic, and/or spatial information on the same cells. The development of new statistical and computational methods in Bioconductor for such data will be facilitated by easy availability of landmark datasets using standard data classes.

RESULTS

We collected, processed, and packaged publicly available landmark datasets from important single-cell multimodal protocols, including CITE-Seq, ECCITE-Seq, SCoPE2, scNMT, 10X Multiome, seqFISH, and G&T. We integrate data modalities via the MultiAssayExperiment Bioconductor class, document and re-distribute datasets as the SingleCellMultiModal package in Bioconductor's Cloud-based ExperimentHub. The result is single-command actualization of landmark datasets from seven single-cell multimodal data generation technologies, without need for further data processing or wrangling in order to analyze and develop methods within Bioconductor's ecosystem of hundreds of packages for single-cell and multimodal data.

CONCLUSIONS

We provide two examples of integrative analyses that are greatly simplified by SingleCellMultiModal. The package will facilitate development of bioinformatic and statistical methods in Bioconductor to meet the challenges of integrating molecular layers and analyzing phenotypic outputs including cell differentiation, activity, and disease.

Activation Profile of Tas2r2, The 26th Human Bitter Taste Receptor

SCOPE

To avoid ingestion of potentially harmful substances humans are equipped with about 25 bitter taste receptor genes (TAS2R) expressed in oral taste cells. Humans exhibit considerable variances in their bitter tasting abilities, which are associated with genetic polymorphisms in bitter taste receptor genes. One of these variant receptor genes, TAS2R2, was initially believed to represent a pseudogene. However, TAS2R2 exists in a putative functional variant within some populations and can therefore be considered as an additional functional bitter taste receptor.

METHODS AND RESULTS

To learn more about the function of the experimentally neglected TAS2R2, we performed a functional screening with 122 bitter compounds. We observed responses with 8 of the 122 bitter substances and identified the substance phenylbutazone as a unique activator of TAS2R2 among the family of TAS2Rs, thus filling one more gap in the array of cognate bitter substances.

CONCLUSIONS

The comprehensive characterization of the receptive range of TAS2R2 allowed the classification into the group of TAS2Rs with a medium number of bitter agonists. The variability of bitter taste and its potential influence on food choice in some human populations might be even higher than assumed. This article is protected by copyright. All rights reserved.

signifinder enables the identification of tumor cell states and cancer expression signatures in bulk, single-cell and spatial transcriptomic data

Over the last decade, many studies and some clinical trials have proposed gene expression signatures as a valuable tool for understanding cancer mechanisms, defining subtypes, monitoring patient prognosis, and therapy efficacy. However, technical and biological concerns about reproducibility have been raised. Technical reproducibility is a major concern: we currently lack a computational implementation of the proposed signatures, which would provide detailed signature definition and assure reproducibility, dissemination, and usability of the classifier. Another concern regards intratumor heterogeneity, which has never been addressed when studying these types of biomarkers using bulk transcriptomics. With the aim of providing a tool able to improve the reproducibility and usability of gene expression signatures, we propose signifinder, an R package that provides the infrastructure to collect, implement, and compare expression-based signatures from cancer literature. The included signatures cover a wide range of biological processes from metabolism and programmed cell death, to morphological changes, such as quantification of epithelial or mesenchymal-like status. Collected signatures can score tumor cell characteristics, such as the predicted response to therapy or the survival association, and can quantify microenvironmental information, including hypoxia and immune response activity. signifinder has been used to characterize tumor samples and to investigate intra-tumor heterogeneity, extending its application to single-cell and spatial transcriptomic data. Through these higher-resolution technologies, it has become increasingly apparent that the single-sample score assessment obtained by transcriptional signatures is conditioned by the phenotypic and genetic intratumor heterogeneity of tumor masses. Since the characteristics of the most abundant cell type or clone might not necessarily predict the properties of mixed populations, signature prediction efficacy is lowered, thus impeding effective clinical diagnostics. Through signifinder, we offer general principles for interpreting and comparing transcriptional signatures, as well as suggestions for additional signatures that would allow for more complete and robust data inferences. We consider signifinder a useful tool to pave the way for reproducibility and comparison of transcriptional signatures in oncology.

Age-Dependent Prebiotic Effects of Soluble Corn Fiber in M-SHIME® Gut Microbial Ecosystems

Soluble corn fiber (SCF) has demonstrated prebiotic effects in clinical studies. Using an in vitro mucosal simulator of the human intestinal microbial ecosystem (M-SHIME^®) model, the effects of SCF treatment on colonic microbiota composition and metabolic activity and on host-microbiome interactions were evaluated using fecal samples from healthy donors of different ages (baby [≤ 2 years], n = 4; adult [18-45 years], n = 2; elderly [70 years], n = 1). During the 3-week treatment period, M-SHIME^® systems were supplemented with SCF daily (baby, 1.5, 3, or 4.5 g/d; adult, 3 or 8.5 g/d; and elderly, 8.5 g/d). M-SHIME^® supernatants were evaluated for their effect on the intestinal epithelial cell barrier and inflammatory responses in lipopolysaccharide. (LPS)-stimulated cells. Additionally, short-chain fatty acid (SCFA) production and microbial community composition were assessed. In the baby and adult models, M-SHIME^® supernatants from SCF treated vessels protected Caco-2 membrane integrity from LPS-induced damage. SCF treatment resulted in the expansion of Bacteroidetes, Firmicutes, and Bifidobacterial, as well as increased SCFA production in all age groups. SCF tended to have the greatest effect on propionate production. These findings demonstrate the prebiotic potential of SCF in babies, adults, and the elderly and provide insight into the mechanisms behind the observed prebiotic effects.

A Bartlett-type correction for likelihood ratio tests with application to testing equality of Gaussian graphical models

This work defines a new correction for the likelihood ratio test for a two-sample problem within the multivariate normal context. This correction applies to decomposable graphical models, where testing equality of distributions can be decomposed into lower dimensional problems.

Effect of packaging in preventing cholesterol autoxidation in milk chocolates for a higher quality and safer shelf-life

Non-enzymatic cholesterol oxidation products (COPs) are nowadays receiving increasing attention in food technology for their potential use as biomarkers of freshness and safety in raw materials and complex food matrices, as well as markers of cholesterol oxidation during the production and shelf-life of end products. Here reported is the investigation of how long three prototype milk chocolates containing whole milk powders (WMPs) of increasing shelf-lives (i.e. 20, 120, and 180 days), could be safely stored in the market by adopting the non-enzymatic COPs as a quality markers. In addition, the protective effect of two different primary packaging, sealed and unsealed ones, in mitigating the generation of non-enzymatic COPs in three prototype milk chocolates after 3, 6, 9, 12 months of shelf-life was assessed to simulate two real storage conditions. Quantifying oxysterols' levels by mass spectrometry, the oxygen impermeable packaging (PLUS) resulted to significantly quench the non-enzymatic COPs production up to 34% as to that found in the same product but with unsealed standard packaging (STD). This study represents one practical application of non-enzymatic COPs as a reliable tool for corrective strategies to prevent food oxidation.

benchdamic: benchmarking of differential abundance methods for microbiome data

SUMMARY

Recently, an increasing number of methodological approaches have been proposed to tackle the complexity of metagenomics and microbiome data. In this scenario, reproducibility and replicability have become two critical issues, and the development of computational frameworks for the comparative evaluations of such methods is of utmost importance. Here, we present benchdamic, a Bioconductor package to benchmark methods for the identification of differentially abundant taxa.

AVAILABILITY AND IMPLEMENTATION

benchdamic is available as an open-source R package through the Bioconductor project at https://bioconductor.org/packages/benchdamic/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Normalization benchmark of ATAC-seq datasets shows the importance of accounting for GC-content effects

The assay for transposase-accessible chromatin using sequencing (ATAC-seq) allows the study of epigenetic regulation of gene expression by assessing chromatin configuration for an entire genome. Despite its popularity, there have been limited studies investigating the analytical challenges related to ATAC-seq data, with most studies leveraging tools developed for bulk transcriptome sequencing. Here, we show that GC-content effects are omnipresent in ATAC-seq datasets. Since the GC-content effects are sample specific, they can bias downstream analyses such as clustering and differential accessibility analysis. We introduce a normalization method based on smooth-quantile normalization within GC-content bins and evaluate it together with 11 different normalization procedures on 8 public ATAC-seq datasets. Accounting for GC-content effects in the normalization is crucial for common downstream ATAC-seq data analyses, improving accuracy and interpretability. Through case studies, we show that exploratory data analysis is essential to guide the choice of an appropriate normalization method for a given dataset.

Moderate intakes of soluble corn fibre or inulin do not cause gastrointestinal discomfort and are well tolerated in healthy children

We investigated the gastrointestinal (GI) tolerance of soluble corn fibre (SCF) compared with inulin in children 3-9 years old. SCF (3-8 g/d for 10d) was tolerated as well as inulin: no differences were identified in stool frequency and consistency, proportion of subjects with at least one loose stool or reporting symptoms during bowel movement. Compared to inulin, 6 g/d of SCF lowered gas severity in children aged 3-5 years old. No differences were noted for alpha and beta diversity, relative abundance of Bacteroidota, Firmicutes, Ruminococcaceae, or the Firmicutes to Bacteroidota ratio. Relative abundance of some specific strains (i.e. Anaerostipes, Bifidobacterium, Fusicatenibacter, Parabacteroides) varied depending on the fibre type and dose level. Fortification at a level of 6-8 g/d of SCF and/or inulin could help addressing the fibre gap without any GI discomfort.

Distribution of TAS2R38 bitter taste receptor phenotype and haplotypes among COVID-19 patients

Bitter taste receptor TAS2R38 is expressed in the respiratory tract and can respond to quorum-sensing molecules produced by pathogens, stimulating the release of nitric oxide, with biocidal activity. TAS2R38 presents two main high-frequency haplotypes: the “taster” PAV and the “non-taster” AVI. Individuals carrying the AVI allele could be at greater risk of infections, including SARS-CoV-2. The aim of this study was to assess the frequency of PAV and AVI alleles in COVID-19 patients with severe or non-severe symptoms compared to healthy subjects to further corroborate, or not, the hypothesis that the PAV allele may act as a protecting factor towards SARS-CoV-2 infection while the AVI one may represent a risk factor. After careful selection, 54 individuals were included in the study and underwent genetic analysis and PROP phenotype assessment. Our investigation could not point out at a significant relationship between single nucleotide polymorphisms responsible for PROP bitterness and presence/severity of SARS-CoV-2 infection, as previous studies suggested. Our results uncouple the direct genetic contribution of rs10246939, rs1726866 and rs713598 on COVID-19, calling for caution when proposing a treatment based on TAS2R38 phenotypes.

SpatialExperiment: infrastructure for spatially-resolved transcriptomics data in R using Bioconductor

SUMMARY

SpatialExperiment is a new data infrastructure for storing and accessing spatially-resolved transcriptomics data, implemented within the R/Bioconductor framework, which provides advantages of modularity, interoperability, standardized operations and comprehensive documentation. Here, we demonstrate the structure and user interface with examples from the 10x Genomics Visium and seqFISH platforms, and provide access to example datasets and visualization tools in the STexampleData, TENxVisiumData and ggspavis packages.

AVAILABILITY AND IMPLEMENTATION

The SpatialExperiment, STexampleData, TENxVisiumData and ggspavis packages are available from Bioconductor. The package versions described in this manuscript are available in Bioconductor version 3.15 onwards.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Receiver operating characteristic estimation and threshold selection criteria in three-class classification problems for clustered data

Statistical evaluation of diagnostic tests, and, more generally, of biomarkers, is a constantly developing field, in which complexity of the assessment increases with the complexity of the design under which data are collected. One particularly prevalent type of data is clustered data, where individual units are naturally nested into clusters. In these cases, Bias can arise from omission, in the evaluation process, of cluster-level effects and/or individual covariates. Focusing on the three-class case and for continuous-valued diagnostic tests, we investigate how to exploit the clustered structure of data within a linear-mixed model approach, both when the assumption of normality holds and when it does not. We provide a method for the estimation of covariate-specific receiver operating characteristic surfaces and discuss methods for the choice of optimal thresholds, proposing three possible estimators. A proof of consistency and asymptotic normality of the proposed threshold estimators is given. All considered methods are evaluated by extensive simulation experiments. As an application, we study the use of the Lysosomal Associated Membrane Protein Family Member 5 gene expression as a biomarker to distinguish among three types of glutamatergic neurons.

Presence of cholesterol oxides in milk chocolates and their correlation with milk powder freshness

Cholesterol oxidation products (COPs) of non-enzymatic origin are mainly found in meat, fish, eggs and milk, mostly originating from the type of feeding, processing and storage. To verify the significance of COPs as biomarkers of cholesterol autoxidation and milk freshness, we quantified them in chocolates containing whole milk powders (WMPs) of increasing shelf-lives (i.e. 20, 120, and 180 days). Non-enzymatic total COPs (both free and esterified) ranged from 256.57 ± 11.97 to 445.82 ± 11.88 ng/g, increasing proportionally to the shelf-life of the WMPs, thus reflecting the ingredients’ freshness. Based on the expected theoretical COPs, the effect of processing was quantitatively less significant in the generation of oxysterols (41–44%) than the contribution of the autoxidation of the WMPs over time (56–59%), pointing to the shelf-life as the primary determinant of COPs. Lastly, we quantified COPs of major commercial milk chocolates on the Italian market, which followed a similar distribution (from 240.79 ± 11.74 to 475.12 ± 12.58 ng/g). Although further replications of this work are needed, this study reports preliminary results and a practical example of a first application of non-enzymatic COPs as markers to further quantify and characterize the nutritional quality and freshness, not only of ingredients but also of composite products.

NewWave: a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA-seq data

Summary

We present NewWave, a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA sequencing data. To achieve scalability, NewWave uses mini-batch optimization and can work with out-of-memory data, enabling users to analyze datasets with millions of cells.

Availability and implementation

NewWave is implemented as an open-source R package available through the Bioconductor project at https://bioconductor.org/packages/NewWave/

Supplementary information

Supplementary data are available at Bioinformatics online.

Oxysterols as Reliable Markers of Quality and Safety in Cholesterol Containing Food Ingredients and Products

Cholesterol is a lipid of high nutritional value that easily undergoes oxidation through enzymatic and non-enzymatic pathways, leading to a wide variety of cholesterol oxidation products (COPs), more commonly named oxysterols. The major oxysterols found in animal products are 7α-hydroxycholesterol, 7β-hydroxycholesterol, 7-ketocholesterol, 5α,6α-epoxycholesterol, 5β,6β-epoxycholesterol, cholestan-3β,5α,6β-triol, and 25-hydroxycholesterol. They are all produced by cholesterol autoxidation, thus belonging to the non-enzymatic oxysterol subfamily, even if 7α-hydroxycholesterol and 25-hydroxycholesterol are, in part, generated enzymatically as well. A further oxysterol of the full enzymatic origin has recently been detected for the first time in milk of both human and bovine origin, namely 27-hydroxycholesterol. Nowadays, gas or liquid chromatography combined to mass spectrometry allows to measure all these oxysterols accurately in raw and in industrially processed food. While non-enzymatic oxysterols often exhibited in vitro relevant cytotoxicity, above all 7β-hydroxycholesterol and 7-ketocholesterol, 27-hydroxycholesterol, as well as 25-hydroxycholesterol, shows a broad spectrum in vitro antiviral activity, inhibition of SARS-CoV-2 included, and might contribute to innate immunity. Quantification of oxysterols was afforded over the years, almost always focused on a few family's compounds. More comprehensive COPs measurements, also including oxysterols of enzymatic origin, are, nowadays, available, which better display the many advantages of systematically adopting this family of compounds as markers of quality, safety, and nutritional value in the selection of ingredients in processing and storage. Regarding foodstuff shelf life, COPs monitoring already provided useful hints for more suitable packaging. The identification of a subset of non-enzymatic and enzymatic oxysterols to be routinely assessed in food production and storage is proposed.

Oxysterols: From redox bench to industry

More and more attention is nowadays given to the possible translational application of a great number of biochemical and biological findings with the involved molecules. This is also the case of cholesterol oxidation products, redox molecules over the last years deeply investigated for their implication in human pathophysiology. Oxysterols of non-enzymatic origin, the excessive increase of which in biological fluids and tissues is of toxicological relevance for their marked pro-oxidant and pro-inflammatory properties, are increasingly applied in clinical biochemistry as molecular markers in the diagnosis and monitoring of several human and veterinary diseases. Conversely, oxysterols of enzymatic origin, the production of which is commonly under physiological regulation, could be considered and tested as promising pharmaceutical agents because of their antiviral, pro-osteogenic and antiadipogenic properties of some of them. Very recently, the quantification of oxysterols of non-enzymatic origin has been adopted in a systematic way to evaluate, monitor and improve the quality of cholesterol-based food ingredients, that are prone to auto-oxidation, as well as their industrial processing and the packaging and the shelf life of the finished food products. The growing translational value of oxysterols is here reviewed in its present and upcoming applications in various industrial fields.

A mouse-specific retrotransposon drives a conserved Cdk2ap1 isoform essential for development

Retrotransposons mediate gene regulation in important developmental and pathological processes. Here, we characterized the transient retrotransposon induction during preimplantation development of eight mammals. Induced retrotransposons exhibit similar preimplantation profiles across species, conferring gene regulatory activities, particularly through long terminal repeat (LTR) retrotransposon promoters. A mouse-specific MT2B2 retrotransposon promoter generates an N-terminally truncated Cdk2ap1ΔN that peaks in preimplantation embryos and promotes proliferation. In contrast, the canonical Cdk2ap1 peaks in mid-gestation and represses cell proliferation. This MT2B2 promoter, whose deletion abolishes Cdk2ap1ΔN production, reduces cell proliferation and impairs embryo implantation, is developmentally essential. Intriguingly, Cdk2ap1ΔN is evolutionarily conserved in sequence and function yet is driven by different promoters across mammals. The distinct preimplantation Cdk2ap1ΔN expression in each mammalian species correlates with the duration of its preimplantation development. Hence, species-specific transposon promoters can yield evolutionarily conserved, alternative protein isoforms, bestowing them with new functions and species-specific expression to govern essential biological divergence.

Food labeling issues for severe food allergic patients

Food allergy carries high importance and responsibility, affecting an estimated 220 million people worldwide. It is a frequent cause of food-induced anaphylaxis, a life-threatening condition requiring a toll of about one death per 50 million people a year worldwide. In order to help patients to identify allergenic foods and thus avoid anaphylactic reactions, 66 countries over the 5 continents require by law that allergenic ingredients must be declared when used in prepackaged foods. Unfortunately, the mandatory allergen list is not uniform, but varies among different countries. The widespread adoption of Precautionary Allergen Labeling (PAL) results in a proliferation of unregulated PALs with different informative statements. In this situation, the need of a scientific consensus on the definition of food allergy and the identification of a tolerable risk with routinely used detection assays, considering not only the eliciting dose but also the food source, is urgent. The aim of this manuscript is: 1) to draw a picture of the global situation in terms of PALs, and 2) to highlight new approaches that could aid in tackling the problem of regulating the labeling of allergens. These include the Voluntary Incidental Trace Allergen Labelling (VITAL) system, which intersects reference doses and labelling decisions, and a direct quantification of trace amounts of allergens at lower limit of detection (LOD) levels in the food itself through proteomics. We here highlight how, although with some limitations, the steady advances in proteomic approaches possess higher sensitivity than the recommended VITAL reference doses, allowing the identification of allergens at much lower LOD levels than VITAL. Considering that each assay used to detect allergen in food products carries method-specific issues, a more comprehensive and harmonized approach implementing both quantitative and qualitative methods could help overcoming the risk stratification approach and the overuse of PALs, offering promise as the field moves forward towards improving consumers' quality of life.

A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex

Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1-3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas-containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities-is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis.

A multimodal cell census and atlas of the mammalian primary motor cortex

Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1-5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

PsiNorm: a scalable normalization for single-cell RNA-seq data

MOTIVATION

Single-cell RNA sequencing (scRNA-seq) enables transcriptome-wide gene expression measurements at single-cell resolution providing a comprehensive view of the compositions and dynamics of tissue and organism development. The evolution of scRNA-seq protocols has led to a dramatic increase of cells throughput, exacerbating many of the computational and statistical issues that previously arose for bulk sequencing. In particular, with scRNA-seq data all the analyses steps, including normalization, have become computationally intensive, both in terms of memory usage and computational time. In this perspective, new accurate methods able to scale efficiently are desirable.

RESULTS

Here, we propose PsiNorm, a between-sample normalization method based on the power-law Pareto distribution parameter estimate. Here, we show that the Pareto distribution well resembles scRNA-seq data, especially those coming from platforms that use unique molecular identifiers. Motivated by this result, we implement PsiNorm, a simple and highly scalable normalization method. We benchmark PsiNorm against seven other methods in terms of cluster identification, concordance and computational resources required. We demonstrate that PsiNorm is among the top performing methods showing a good trade-off between accuracy and scalability. Moreover, PsiNorm does not need a reference, a characteristic that makes it useful in supervised classification settings, in which new out-of-sample data need to be normalized.

AVAILABILITY AND IMPLEMENTATION

PsiNorm is implemented in the scone Bioconductor package and available at https://bioconductor.org/packages/scone/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Potential Valorization of Hazelnut Shells through Extraction, Purification and Structural Characterization of Prebiotic Compounds: A Critical Review

Hazelnuts are one of the most widely consumed nuts, but their production creates large quantities of by-products, especially shells, that could be upcycled into much more valuable products. Recent studies have shown that hazelnut shell hemicellulose is particularly rich in compounds that are potential precursors of xylooligosaccharides and arabino-xylooligosaccharides ((A)XOS), previously defined as emerging prebiotics very beneficial for human health. The production of these compounds on an industrial scale-up could have big consequences on the functional foods market. However, to produce (A)XOS from a lignocellulosic biomass, such as hazelnut shell, is not easy. Many methods for the extraction and the purification of these prebiotics have been developed, but they all have different efficiencies and consequences, including on the chemical structure of the obtained (A)XOS. The latter, in turn, is strongly correlated to the nutritional effects they have on health, which is why the optimization of the structural characterization process is also necessary. Therefore, this review aims to summarize the progress made by research in this field, so as to contribute to the exploitation of hazelnut waste streams through a circular economy approach, increasing the value of this biomass through the production of new functional ingredients.

Per-sample standardization and asymmetric winsorization lead to accurate clustering of RNA-seq expression profiles

MOTIVATION

Data transformations are an important step in the analysis of RNA-seq data. Nonetheless, the impact of transformation on the outcome of unsupervised clustering procedures is still unclear.

RESULTS

Here, we present an Asymmetric Winsorization per Sample Transformation (AWST), which is robust to data perturbations and removes the need for selecting the most informative genes prior to sample clustering. Our procedure leads to robust and biologically meaningful clusters both in bulk and in single-cell applications.

AVAILABILITY

The AWST method is available at https://github.com/drisso/awst. The code to reproduce the analyses is available at https://github.com/drisso/awst\_analysis.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Effect of industrial processing and storage procedures on oxysterols in milk and milk products

Oxysterols are products of enzymatic and/or chemical cholesterol oxidation. While some of the former possess broad antiviral activities, the latter mostly originate from the deterioration of the nutritional value of foodstuff after exposure to heat, light, radiation and oxygen, raising questions about their potential health risks. We evaluated the presence of selected oxysterols in bovine colostrum and monitored the evolution of their cholesterol ratio throughout an entire industrial-scale milk production chain and after industrially employed storage procedures of milk powders. We report here for the first time the presence of high levels of the enzymatic oxysterol 27-hydroxycholesterol (27OHC) in concentrations of antiviral interest in bovine colostrum (87.04 ng mL^-1) that decreased during the first postpartum days (56.35 ng mL^-1). Of note, this oxysterol is also observed in milk and milk products and is not negatively affected by industrial processing or storage. We further highlight an exponential increase of the non-enzymatic oxysterols 7β-hydroxycholesterol (7βOHC) and 7-ketocholesterol (7KC) in both whole (WMPs) and skimmed milk powders (SMPs) during prolonged storage, confirming their role as reliable biomarkers of cholesterol oxidation over time: after 12 months, 7βOHC reached in both SMPs and WMPs amounts that have been found to be potentially toxic in vitro (265.46 ng g^-1 and 569.83 ng g^-1, respectively). Interestingly, industrial processes appeared to affect the generation of 7βOHC and 7KC differently, depending on the presence of fat in the product: while their ratios increased significantly after skimming and processing of skimmed milk and milk products, this was not observed after processing whole milk and milk cream.

A spatially resolved brain region- and cell type-specific isoform atlas of the postnatal mouse brain

Splicing varies across brain regions, but the single-cell resolution of regional variation is unclear. We present a single-cell investigation of differential isoform expression (DIE) between brain regions using single-cell long-read sequencing in mouse hippocampus and prefrontal cortex in 45 cell types at postnatal day 7 ( www.isoformAtlas.com ). Isoform tests for DIE show better performance than exon tests. We detect hundreds of DIE events traceable to cell types, often corresponding to functionally distinct protein isoforms. Mostly, one cell type is responsible for brain-region specific DIE. However, for fewer genes, multiple cell types influence DIE. Thus, regional identity can, although rarely, override cell-type specificity. Cell types indigenous to one anatomic structure display distinctive DIE, e.g. the choroid plexus epithelium manifests distinct transcription-start-site usage. Spatial transcriptomics and long-read sequencing yield a spatially resolved splicing map. Our methods quantify isoform expression with cell-type and spatial resolution and it contributes to further our understanding of how the brain integrates molecular and cellular complexity.

Normalization of Single-Cell RNA-Seq Data

Normalization is an important step in the analysis of single-cell RNA-seq data. While no single method outperforms all others in all datasets, the choice of normalization can have profound impact on the results. Data-driven metrics can be used to rank normalization methods and select the best performers. Here, we show how to use R/Bioconductor to calculate normalization factors, apply them to compute normalized data, and compare several normalization approaches. Finally, we briefly show how to perform downstream analysis steps on the normalized data.

mbkmeans: Fast clustering for single cell data using mini-batch k-means

Single-cell RNA-Sequencing (scRNA-seq) is the most widely used high-throughput technology to measure genome-wide gene expression at the single-cell level. One of the most common analyses of scRNA-seq data detects distinct subpopulations of cells through the use of unsupervised clustering algorithms. However, recent advances in scRNA-seq technologies result in current datasets ranging from thousands to millions of cells. Popular clustering algorithms, such as k-means, typically require the data to be loaded entirely into memory and therefore can be slow or impossible to run with large datasets. To address this problem, we developed the mbkmeans R/Bioconductor package, an open-source implementation of the mini-batch k-means algorithm. Our package allows for on-disk data representations, such as the common HDF5 file format widely used for single-cell data, that do not require all the data to be loaded into memory at one time. We demonstrate the performance of the mbkmeans package using large datasets, including one with 1.3 million cells. We also highlight and compare the computing performance of mbkmeans against the standard implementation of k-means and other popular single-cell clustering methods. Our software package is available in Bioconductor at https://bioconductor.org/packages/mbkmeans.

Alteration, Reduction and Taste Loss: Main Causes and Potential Implications on Dietary Habits

Our sense of taste arises from the sensory information generated after compounds in the oral cavity and oropharynx activate taste receptor cells situated on taste buds. This produces the perception of sweet, bitter, salty, sour, or umami stimuli, depending on the chemical nature of the tastant. Taste impairments (dysgeusia) are alterations of this normal gustatory functioning that may result in complete taste losses (ageusia), partial reductions (hypogeusia), or over-acuteness of the sense of taste (hypergeusia). Taste impairments are not life-threatening conditions, but they can cause sufficient discomfort and lead to appetite loss and changes in eating habits, with possible effects on health. Determinants of such alterations are multiple and consist of both genetic and environmental factors, including aging, exposure to chemicals, drugs, trauma, high alcohol consumption, cigarette smoking, poor oral health, malnutrition, and viral upper respiratory infections including influenza. Disturbances or loss of smell, taste, and chemesthesis have also emerged as predominant neurological symptoms of infection by the recent Coronavirus disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus strain 2 (SARS-CoV-2), as well as by previous both endemic and pandemic coronaviruses such as Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and SARS-CoV. This review is focused on the main causes of alteration, reduction, and loss of taste and their potential repercussion on dietary habits and health, with a special focus on the recently developed hypotheses regarding the mechanisms through which SARS-CoV-2 might alter taste perception.

Abstract 622: Rapid non-uniform adaptation to conformation-specific KRAS G12Cinhibition

KRAS GTPases are activated in one-third of cancers and KRAS G12C is the most common activating alteration in lung adenocarcinoma. KRAS G12C-specific inhibitors (G12Ci) are in Phase-I clinical trials and early data show only partial responses in lung cancer patients. How cancer cells bypass inhibition, to prevent maximal responses to therapy, is not understood. Because KRAS G12C cycles between an active and inactive conformation, and the covalent G12Ci only bind to the latter, we tested whether isogenic cell populations respond non-uniformly by studying the effect of treatment at a single-cell resolution. Using single-cell RNA sequencing and a fluorescent quiescence biosensor, we show that shortly after treatment, most cancer cells are sequestered in a quiescent state with low KRAS activity, while a small population reactivates KRAS to resume proliferation. This rapid divergent response is due to synthesis of new, drug-free KRAS protein, resulting from increased KRAS transcription in response to suppressed MAPK signaling. Combining cell fate-specific gene expressions and results from a CRISPR-Cas9 screen, we identified that adaptive signals such as epidermal growth-factor receptor and aurora kinase A signaling modulate the heterogeneous response to treatment with G12Ci. These upstream signals help to maintain new KRAS G12C protein in its active, drug-insensitive state, which restores KRAS signaling and transcriptional output in a subset of cells to allow escape from G12Ci-induced quiescence. Cells without these adaptive changes (or cells where they are pharmacologically inhibited) remain sensitive to G12Ci treatment, because new KRAS G12C is either not available, or it exists in its inactive, drug-sensitive state. Combined inhibition of these adaptive signals along with KRAS G12C produced more potent antitumor effects in xenograft models. The direct targeting of KRAS oncoproteins has been a longstanding objective in precision oncology. Our study uncovers a flexible non-uniform fitness mechanism that enables groups of cells within a population to rapidly bypass the effect of treatment. This adaptive process must be overcome to maximize the therapeutic potential of conformation-specific KRAS G12C inhibitors in the clinic.

Citation Format: Jenny Y. Xue, Yulei Zhao, Jordan Aronowitz, Trang T. Mai, Alberto Vides, Besnik Qeriqi, Dongsung Kim, Chuanchuan Li, Elisa de Stanchina, Linas Mazutis, Davide Risso, Piro Lito. Rapid non-uniform adaptation to conformation-specific KRAS G12Cinhibition [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 622.

Assessment of statistical methods from single cell, bulk RNA-seq, and metagenomics applied to microbiome data

BACKGROUND

The correct identification of differentially abundant microbial taxa between experimental conditions is a methodological and computational challenge. Recent work has produced methods to deal with the high sparsity and compositionality characteristic of microbiome data, but independent benchmarks comparing these to alternatives developed for RNA-seq data analysis are lacking.

RESULTS

We compare methods developed for single-cell and bulk RNA-seq, and specifically for microbiome data, in terms of suitability of distributional assumptions, ability to control false discoveries, concordance, power, and correct identification of differentially abundant genera. We benchmark these methods using 100 manually curated datasets from 16S and whole metagenome shotgun sequencing.

CONCLUSIONS

The multivariate and compositional methods developed specifically for microbiome analysis did not outperform univariate methods developed for differential expression analysis of RNA-seq data. We recommend a careful exploratory data analysis prior to application of any inferential model and we present a framework to help scientists make an informed choice of analysis methods in a dataset-specific manner.

Non-neuronal expression of SARS-CoV-2 entry genes in the olfactory system suggests mechanisms underlying COVID-19-associated anosmia

Altered olfactory function is a common symptom of COVID-19, but its etiology is unknown. A key question is whether SARS-CoV-2 (CoV-2) - the causal agent in COVID-19 - affects olfaction directly, by infecting olfactory sensory neurons or their targets in the olfactory bulb, or indirectly, through perturbation of supporting cells. Here we identify cell types in the olfactory epithelium and olfactory bulb that express SARS-CoV-2 cell entry molecules. Bulk sequencing demonstrated that mouse, non-human primate and human olfactory mucosa expresses two key genes involved in CoV-2 entry, ACE2 and TMPRSS2. However, single cell sequencing revealed that ACE2 is expressed in support cells, stem cells, and perivascular cells, rather than in neurons. Immunostaining confirmed these results and revealed pervasive expression of ACE2 protein in dorsally-located olfactory epithelial sustentacular cells and olfactory bulb pericytes in the mouse. These findings suggest that CoV-2 infection of non-neuronal cell types leads to anosmia and related disturbances in odor perception in COVID-19 patients.

Performance Assessment and Selection of Normalization Procedures for Single-Cell RNA-Seq

Systematic measurement biases make normalization an essential step in single-cell RNA sequencing (scRNA-seq) analysis. There may be multiple competing considerations behind the assessment of normalization performance, of which some may be study specific. We have developed "scone"- a flexible framework for assessing performance based on a comprehensive panel of data-driven metrics. Through graphical summaries and quantitative reports, scone summarizes trade-offs and ranks large numbers of normalization methods by panel performance. The method is implemented in the open-source Bioconductor R software package scone. We show that top-performing normalization methods lead to better agreement with independent validation data for a collection of scRNA-seq datasets. scone can be downloaded at http://bioconductor.org/packages/scone/.

Orchestrating single-cell analysis with Bioconductor

Recent technological advancements have enabled the profiling of a large number of genome-wide features in individual cells. However, single-cell data present unique challenges that require the development of specialized methods and software infrastructure to successfully derive biological insights. The Bioconductor project has rapidly grown to meet these demands, hosting community-developed open-source software distributed as R packages. Featuring state-of-the-art computational methods, standardized data infrastructure and interactive data visualization tools, we present an overview and online book (https://osca.bioconductor.org) of single-cell methods for prospective users.

Rapid non-uniform adaptation to conformation-specific KRAS(G12C) inhibition

KRAS GTPases are activated in one-third of cancers, and KRAS(G12C) is one of the most common activating alterations in lung adenocarcinoma1,2. KRAS(G12C) inhibitors3,4 are in phase-I clinical trials and early data show partial responses in nearly half of patients with lung cancer. How cancer cells bypass inhibition to prevent maximal response to therapy is not understood. Because KRAS(G12C) cycles between an active and inactive conformation4-6, and the inhibitors bind only to the latter, we tested whether isogenic cell populations respond in a non-uniform manner by studying the effect of treatment at a single-cell resolution. Here we report that, shortly after treatment, some cancer cells are sequestered in a quiescent state with low KRAS activity, whereas others bypass this effect to resume proliferation. This rapid divergent response occurs because some quiescent cells produce new KRAS(G12C) in response to suppressed mitogen-activated protein kinase output. New KRAS(G12C) is maintained in its active, drug-insensitive state by epidermal growth factor receptor and aurora kinase signalling. Cells without these adaptive changes-or cells in which these changes are pharmacologically inhibited-remain sensitive to drug treatment, because new KRAS(G12C) is either not available or exists in its inactive, drug-sensitive state. The direct targeting of KRAS oncoproteins has been a longstanding objective in precision oncology. Our study uncovers a flexible non-uniform fitness mechanism that enables groups of cells within a population to rapidly bypass the effect of treatment. This adaptive process must be overcome if we are to achieve complete and durable responses in the clinic.

Abstract LB-A04: Rapid non-uniform adaptation to conformation-specific KRAS G12C inhibition

KRAS GTPases are activated in one-third of cancers and KRAS G12C is the most common activating alteration in lung adenocarcinoma. KRAS G12C inhibitors are in Phase-I clinical trials and early data show only partial responses in lung cancer patients. How cancer cells bypass inhibition, to prevent maximal responses to therapy, is not understood. Because KRAS G12C cycles between an active and inactive conformation, and the inhibitors only bind to the latter, we hypothesized that isogenic cell populations respond non-uniformly. Here we studied the effect of treatment at the single cell level and showed that shortly after treatment, some cancer cells were sequestered in a quiescent state with low KRAS activity, while others reactivated KRAS to resume proliferation. By combining cell fate-specific gene expressions and results from a CRISPR-Cas9 screen, we identified that this rapid divergent response is due to new KRAS G12C produced in response to suppressed MAPK output. Upstream-acting adaptive signals, such as epidermal growth-factor receptor and aurora kinase signaling, maintain new KRAS G12C protein in its active/drug-insensitive state to restore KRAS output. Cells without these adaptive changes (or cells where they are pharmacologically inhibited) remain sensitive to drug treatment, because new KRAS G12C is either not available, or it exists in its inactive/drug-sensitive state. Combined inhibition of these adaptive signals along with KRAS G12C produced more potent antitumor effects in vivo. Our study uncovers a flexible non-uniform fitness mechanism that enables groups of cells within a population to rapidly bypass the effect of treatment. This adaptive process must be overcome to maximize the therapeutic potential of conformation-specific KRAS G12C inhibitors in the clinic.

Citation Format: Jenny Xue, Yulei Zhao, Jordan Aronowitz, Trang T Mai, Alberto Vides, Besnik Qeriqi, Dongsung Kim, Chuanchuan Li, Elisa de Stanchina, Linas Mazutis, Davide Risso, Piro Lito. Rapid non-uniform adaptation to conformation-specific KRAS G12C inhibition [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr LB-A04. doi:10.1158/1535-7163.TARG-19-LB-A04

The Human-Specific BOLA2 Duplication Modifies Iron Homeostasis and Anemia Predisposition in Chromosome 16p11.2 Autism Individuals

Human-specific duplications at chromosome 16p11.2 mediate recurrent pathogenic 600 kbp BP4-BP5 copy-number variations, which are among the most common genetic causes of autism. These copy-number polymorphic duplications are under positive selection and include three to eight copies of BOLA2, a gene involved in the maturation of cytosolic iron-sulfur proteins. To investigate the potential advantage provided by the rapid expansion of BOLA2, we assessed hematological traits and anemia prevalence in 379,385 controls and individuals who have lost or gained copies of BOLA2: 89 chromosome 16p11.2 BP4-BP5 deletion carriers and 56 reciprocal duplication carriers in the UK Biobank. We found that the 16p11.2 deletion is associated with anemia (18/89 carriers, 20%, p = 4e-7, OR = 5), particularly iron-deficiency anemia. We observed similar enrichments in two clinical 16p11.2 deletion cohorts, which included 6/63 (10%) and 7/20 (35%) unrelated individuals with anemia, microcytosis, low serum iron, or low blood hemoglobin. Upon stratification by BOLA2 copy number, our data showed an association between low BOLA2 dosage and the above phenotypes (8/15 individuals with three copies, 53%, p = 1e-4). In parallel, we analyzed hematological traits in mice carrying the 16p11.2 orthologous deletion or duplication, as well as Bola2^+/- and Bola2^-/- animals. The Bola2-deficient mice and the mice carrying the deletion showed early evidence of iron deficiency, including a mild decrease in hemoglobin, lower plasma iron, microcytosis, and an increased red blood cell zinc-protoporphyrin-to-heme ratio. Our results indicate that BOLA2 participates in iron homeostasis in vivo, and its expansion has a potential adaptive role in protecting against iron deficiency.

Abstract 909: Single-cell transcriptomic profiling of non-small cell lung cancer uncovers inter- and intracell population structure across TCGA lung adenocarcinoma and lung squamous cancer subtypes

Lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) are the most prevalent types of non-all cell lung cancer (NSCLC), a leading cause of cancer death worldwide. In this study, we analyzed the transcriptomes of ~45,000 single cells (scRNA) from 13 NSCLC patients, including 5 LUAD cases which were collected and profiled at our institution. To correlate genomes and transcriptomes we performed Whole-Genome Sequencing (WGS) on 3 of these 5 LUAD cases. By comparing tumor tissue with matched adjacent non-malignant lung tissue we are able to confidently distinguish 13 cell-type specific clusters that unambiguously match previously characterized lineages. We developed algorithms for the identification of malignant cells derived from tumor tissue through scRNA analysis of copy number alterations and single nucleotide variants (SNV). Joint analysis of WGS and scRNA confirmed an enrichment of tobacco-associated SNVs among malignant cells of the tumor. Stromal cell types demonstrated consistent expression patterns across cases, while malignant cells demonstrated both inter- and intra-tumoral heterogeneity in their expression of signatures related to GPCR signaling, 3’ UTR mediated translational regulation, and cell-cell junction organization. In particular, one case displayed a unique pattern of intra-tumoral heterogeneity, as a subset of malignant cells robustly express a marker of pulmonary neuroendocrine cells, CGRP. Employing immunohistochemistry, the spatial organization of these malignant cells is revealed to be mutually exclusive within the tumor microenvironment and overlapping in expression of clinical markers of small-cell lung cancer. Finally, we deconvolved bulk TCGA LUAD and LUSC gene expression samples and analyzed the relationship between cell type specific gene expression in cell types of the lung and passenger mutation topographies. Our results provide insight into the molecular and clinical correlates of deconvolved NSCLC transcriptomes and provide a novel methodology with which to explore genomic variation at a single cell resolution. Furthermore, our dataset provides a resource for illuminating cancer-cell transcriptional changes and revealing key molecular drivers of tumor-stromal interactions in lung cancer.

Citation Format: Kofi E. Gyan, Aditya Deshpande, Shaham Beg, Huasong Tian, Joel Rosiene, Marlon Stoeckius, Peter Smibert, Davide Risso, Juan Miguel Mosquera, Marcin Imielinski. Single-cell transcriptomic profiling of non-small cell lung cancer uncovers inter- and intracell population structure across TCGA lung adenocarcinoma and lung squamous cancer subtypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 909.

Epigenetic evolution and lineage histories of chronic lymphocytic leukaemia

Genetic and epigenetic intra-tumoral heterogeneity cooperate to shape the evolutionary course of cancer¹. Chronic lymphocytic leukaemia (CLL) is a highly informative model for cancer evolution as it undergoes substantial genetic diversification and evolution after therapy^2,3. The CLL epigenome is also an important disease-defining feature^4,5, and growing populations of cells in CLL diversify by stochastic changes in DNA methylation known as epimutations⁶. However, previous studies using bulk sequencing methods to analyse the patterns of DNA methylation were unable to determine whether epimutations affect CLL populations homogeneously. Here, to measure the epimutation rate at single-cell resolution, we applied multiplexed single-cell reduced-representation bisulfite sequencing to B cells from healthy donors and patients with CLL. We observed that the common clonal origin of CLL results in a consistently increased epimutation rate, with low variability in the cell-to-cell epimutation rate. By contrast, variable epimutation rates across healthy B cells reflect diverse evolutionary ages across the trajectory of B cell differentiation, consistent with epimutations serving as a molecular clock. Heritable epimutation information allowed us to reconstruct lineages at high-resolution with single-cell data, and to apply this directly to patient samples. The CLL lineage tree shape revealed earlier branching and longer branch lengths than in normal B cells, reflecting rapid drift after the initial malignant transformation and a greater proliferative history. Integration of single-cell bisulfite sequencing analysis with single-cell transcriptomes and genotyping confirmed that genetic subclones mapped to distinct clades, as inferred solely on the basis of epimutation information. Finally, to examine potential lineage biases during therapy, we profiled serial samples during ibrutinib-associated lymphocytosis, and identified clades of cells that were preferentially expelled from the lymph node after treatment, marked by distinct transcriptional profiles. The single-cell integration of genetic, epigenetic and transcriptional information thus charts the lineage history of CLL and its evolution with therapy.

Shank3 modulates sleep and expression of circadian transcription factors

Autism Spectrum Disorder (ASD) is the most prevalent neurodevelopmental disorder in the United States and often co-presents with sleep problems. Sleep problems in ASD predict the severity of ASD core diagnostic symptoms and have a considerable impact on the quality of life of caregivers. Little is known, however, about the underlying molecular mechanisms of sleep problems in ASD. We investigated the role of Shank3, a high confidence ASD gene candidate, in sleep architecture and regulation. We show that mice lacking exon 21 of Shank3 have problems falling asleep even when sleepy. Using RNA-seq we show that sleep deprivation increases the differences in prefrontal cortex gene expression between mutants and wild types, downregulating circadian transcription factors Per3, Bhlhe41, Hlf, Tef, and Nr1d1. Shank3 mutants also have trouble regulating wheel-running activity in constant darkness. Overall, our study shows that Shank3 is an important modulator of sleep and clock gene expression.

Complementary networks of cortical somatostatin interneurons enforce layer specific control

The neocortex is functionally organized into layers. Layer four receives the densest bottom up sensory inputs, while layers 2/3 and 5 receive top down inputs that may convey predictive information. A subset of cortical somatostatin (SST) neurons, the Martinotti cells, gate top down input by inhibiting the apical dendrites of pyramidal cells in layers 2/3 and 5, but it is unknown whether an analogous inhibitory mechanism controls activity in layer 4. Using high precision circuit mapping, in vivo optogenetic perturbations, and single cell transcriptional profiling, we reveal complementary circuits in the mouse barrel cortex involving genetically distinct SST subtypes that specifically and reciprocally interconnect with excitatory cells in different layers: Martinotti cells connect with layers 2/3 and 5, whereas non-Martinotti cells connect with layer 4. By enforcing layer-specific inhibition, these parallel SST subnetworks could independently regulate the balance between bottom up and top down input.