Cell annotation using scRNA-seq data: A protein-protein interaction network approach.

Pathway analysis is an important step in the interpretation of single cell transcriptomic data, as it provides powerful information to detect which cellular processes are active in each individual cell. We have recently developed a protein-protein interaction network-based framework to quantify pluripotency associated pathways from scRNA-seq data. On this occasion, we extend this approach to quantify the activity of a pathway associated with any biological process, or even any list of genes. A systems-level characterization of pathway activities across multiple cell types provides a broadly applicable tool for the analysis of pathways in both healthy and disease conditions. Dysregulated cellular functions are a hallmark of a wide spectrum of human disorders, including cancer and autoimmune diseases. Here, we illustrate our method by analyzing various biological processes in healthy and cancer breast samples. Using this approach we found that tumor breast cells, even when they form a single group in the UMAP space, keep diverse biological programs active in a differentiated manner within the cluster.•We implement a protein-protein interaction network-based approach to quantify the activity of different biological processes.•The methodology can be used for cell annotation in scRNA-seq studies and is freely available as R package.

ORIGINS: A protein network-based approach to quantify cell pluripotency from scRNA-seq data.

Trajectory inference is a common application of scRNA-seq data. However, it is often necessary to previously determine the origin of the trajectories, the stem or progenitor cells. In this work, we propose a computational tool to quantify pluripotency from single cell transcriptomics data. This approach uses the protein-protein interaction (PPI) network associated with the differentiation process as a scaffold and the gene expression matrix to calculate a score that we call differentiation activity. This score reflects how active the differentiation network is in each cell. We benchmark the performance of our algorithm with two previously published tools, LandSCENT (Chen et al., 2019) and CytoTRACE (Gulati et al., 2020), for four healthy human data sets: breast, colon, hematopoietic and lung. We show that our algorithm is more efficient than LandSCENT and requires less RAM memory than the other programs. We also illustrate a complete workflow from the count matrix to trajectory inference using the breast data set.•ORIGINS is a methodology to quantify pluripotency from scRNA-seq data implemented as a freely available R package.•ORIGINS uses the protein-protein interaction network associated with differentiation and the data set expression matrix to calculate a score (differentiation activity) that quantifies pluripotency for each cell.

A new analogue of islet neogenesis associated protein with higher structural and plasma stability.

Islet Neogenesis Associated Protein pentadecapeptide (INGAP-PP) increases ß-cell mass and function in experimental animals. A short clinical trial also yielded promising results. However, HTD4010, a new peptide derived from INGAP-PP, was developed in order to optimize its specific effects by minimizing its side effects. To study and compare the tertiary structure, stability dynamics, and plasma stability of HTD4010, an INGAP-PP analogue. Both peptides were pre-incubated in human, rat and mouse plasma at 37 °C, and their presence was identified and quantified by high performance liquid chromatography at different time-points. GROMACS 2019 package and the Gromos 54A7 force field were used to evaluate overall correlated motion of the peptide molecule during molecular dynamics simulation by essential dynamics. HTD4010 exhibited significantly larger plasma stability than INGAP-PP, and its structural stability was almost 3.36-fold higher than INGAP-PP. These results suggest that HTD4010 may facilitate longer tissue interaction, thereby developing higher potential biological effects. If so, HTD4010 may become a promising therapeutic agent to treat people with diabetes. Communicated by Ramaswamy H. Sarma.

Cooperativity to increase Turing pattern space for synthetic biology.

It is hard to bridge the gap between mathematical formulations and biological implementations of Turing patterns, yet this is necessary for both understanding and engineering these networks with synthetic biology approaches. Here, we model a reaction-diffusion system with two morphogens in a monostable regime, inspired by components that we recently described in a synthetic biology study in mammalian cells.1 The model employs a single promoter to express both the activator and inhibitor genes and produces Turing patterns over large regions of parameter space, using biologically interpretable Hill function reactions. We applied a stability analysis and identified rules for choosing biologically tunable parameter relationships to increase the likelihood of successful patterning. We show how to control Turing pattern sizes and time evolution by manipulating the values for production and degradation relationships. More importantly, our analysis predicts that steep dose-response functions arising from cooperativity are mandatory for Turing patterns. Greater steepness increases parameter space and even reduces the requirement for differential diffusion between activator and inhibitor. These results demonstrate some of the limitations of linear scenarios for reaction-diffusion systems and will help to guide projects to engineer synthetic Turing patterns.

An insight into the transcriptome of the digestive tract of the bloodsucking bug, Rhodnius prolixus.

The bloodsucking hemipteran Rhodnius prolixus is a vector of Chagas' disease, which affects 7-8 million people today in Latin America. In contrast to other hematophagous insects, the triatomine gut is compartmentalized into three segments that perform different functions during blood digestion. Here we report analysis of transcriptomes for each of the segments using pyrosequencing technology. Comparison of transcript frequency in digestive libraries with a whole-body library was used to evaluate expression levels. All classes of digestive enzymes were highly expressed, with a predominance of cysteine and aspartic proteinases, the latter showing a significant expansion through gene duplication. Although no protein digestion is known to occur in the anterior midgut (AM), protease transcripts were found, suggesting secretion as pro-enzymes, being possibly activated in the posterior midgut (PM). As expected, genes related to cytoskeleton, protein synthesis apparatus, protein traffic, and secretion were abundantly transcribed. Despite the absence of a chitinous peritrophic membrane in hemipterans - which have instead a lipidic perimicrovillar membrane lining over midgut epithelia - several gut-specific peritrophin transcripts were found, suggesting that these proteins perform functions other than being a structural component of the peritrophic membrane. Among immunity-related transcripts, while lysozymes and lectins were the most highly expressed, several genes belonging to the Toll pathway - found at low levels in the gut of most insects - were identified, contrasting with a low abundance of transcripts from IMD and STAT pathways. Analysis of transcripts related to lipid metabolism indicates that lipids play multiple roles, being a major energy source, a substrate for perimicrovillar membrane formation, and a source for hydrocarbons possibly to produce the wax layer of the hindgut. Transcripts related to amino acid metabolism showed an unanticipated priority for degradation of tyrosine, phenylalanine, and tryptophan. Analysis of transcripts related to signaling pathways suggested a role for MAP kinases, GTPases, and LKBP1/AMP kinases related to control of cell shape and polarity, possibly in connection with regulation of cell survival, response of pathogens and nutrients. Together, our findings present a new view of the triatomine digestive apparatus and will help us understand trypanosome interaction and allow insights into hemipteran metabolic adaptations to a blood-based diet.

Genetically encoded sender-receiver system in 3D mammalian cell culture.

Engineering spatial patterning in mammalian cells, employing entirely genetically encoded components, requires solving several problems. These include how to code secreted activator or inhibitor molecules and how to send concentration-dependent signals to neighboring cells, to control gene expression. The Madin-Darby Canine Kidney (MDCK) cell line is a potential engineering scaffold as it forms hollow spheres (cysts) in 3D culture and tubulates in response to extracellular hepatocyte growth factor (HGF). We first aimed to graft a synthetic patterning system onto single developing MDCK cysts. We therefore developed a new localized transfection method to engineer distinct sender and receiver regions. A stable reporter line enabled reversible EGFP activation by HGF and modulation by a secreted repressor (a truncated HGF variant, NK4). By expanding the scale to wide fields of cysts, we generated morphogen diffusion gradients, controlling reporter gene expression. Together, these components provide a toolkit for engineering cell-cell communication networks in 3D cell culture.

Peri-ictal complexity loss as determined by approximate entropy analysis in the electrocorticogram obtained from chronic subdural recordings in patients with refractory temporal lobe epilepsy

RATIONALE: The development of closed-loop devices suitable for use in the treatment of epileptic patients would very likely rely on the adequate development of paradigms able to forecast the occurrence of seizures. In this paper, we studied the usefulness of approximate enthropy, of a non-linear paradigm, in this patient population. METHODS: We applied approximate entropy (ApEn) analysis to study the variability in the complexity of the peri-ictal electrocorticogram (ECoG) of patients with refractory epileptic seizures of the temporal lobe origin. Three patients were implanted with chronic subdural grids. The ApEn algorithm measured the complexity of interictal, peri-ictal and ictal phases. We selected one representative channel disclosing interictal activity for each patient and two channels per patient with ictal recordings. RESULTS: In all patients, we found one channel where the interictal activity registered in the ECoG was associated with high complexity and where ApEn was higher than 0.59. But in the other two channels, for each patient that presented interictal/ictal transitions, clinical manifestations of epileptic seizures occurred around 3.5 seconds after the entropy drop, when entropy was below 0.5. In contrast, when entropy was higher than 0.5, clinical manifestation occurred 9.5 seconds after the entropy drop. The 3.5 seconds shorter delay possibly indicates focal activity in the channel analyzed. CONCLUSIONS: Our results suggest that ApEn may be a useful instrument for early detection of epileptic activity. Its application may be indicated for prevention and diagnosis of epileptic seizures.

RACIONAL: O desenvolvimento de aparatos retroalimentáveis para o tratamento de pacientes epilépticos dependerá em grande parte do desenvolvimento adequado de paradigmas que possam antever as crises. Neste trabalho, estudamos a utilidade da entropia aproximada (ApEn), um paradigma não-linear, em pacientes portadores de epilepsia. MÉTODOS: Aplicamos a análise de entropia aproximada (ApEn) no estudo de variabilidade da complexidade do eletrocorticograma (ECoG) de pacientes com epilepsia refratária com origem no lobo temporal. Três pacientes foram implantados com matrizes de eletrodos subdurais. O algoritmo ApEn mediu a complexidade das fases interictal, peri-ictal e ictal. Selecionamos um canal representativo de cada paciente manifestando atividade interictal e dois canais de cada paciente com registro ictal. RESULTADOS: Em cada paciente, encontramos um canal cuja atividade interictal registrada no ECoG foi associada a alta complexidade com ApEn maior que 0.59. Nos outros dois canais, para cada paciente que apresentou transição interictal/ictal, as manifestações clínicas das crises epilépticas ocorreram cerca de 3.5 segundos depois após a queda da entropia abaixo de 0.5. Em comparação, quando a entropia foi maior que 0.5, as manifestações clínicas ocorreram 9,5 segundos após a queda da entropia. A curta latência (3.5 segundos) indicou possivelmente o local de início da atividade focal. CONCLUSÕES: Nossos resultados sugerem que ApEn pode ser um instrumento útil na detecção precoce da atividade epiléptica. Sua aplicação pode estar indicada na prevenção ou diagnóstico das crises epilépticas.