Biology subjects

Marques, J. C.

Publications and source records attributed to Marques, J. C..

5 recordsLinked to original sources

bioRxiv2025

Beyond the known cuts: trypsin specificity in native proteins

Trypsin is a serine protease that plays a pivotal role in protein digestion, being extensively used in various proteomics workflows due to its cleavage profile and specificity. Understanding trypsins enzymatic behavior is thus critical. We have employed Above-Filter Digestion Proteomics (AFDIP) to investigate trypsins cleavage preferences in HeLa cell lysates, preserving the proteins native state. We quantified over 18,000 unique peptides and correlated their emergence rates with cleavage window sequence motifs and physicochemical properties. Contrary to previous studies performed on denatured proteomes, we found that in native proteins cleavages at lysine residues were more abundant and faster than at arginine residues, and that physicochemical properties of the peptides affected their emergence times. These findings may need to be taken into account when interpreting the results of limited proteolysis experiments as well as when designing a food protein with extremely fast digestion times.

biochemistry↗

bioRxiv2024

Megabouts: a flexible pipeline for zebrafish locomotion analysis

Accurate quantification of animal behavior is crucial for advancing neuroscience and for defining reliable physiological markers. We introduce Megabouts (megabouts.ai), a software package standardizing zebrafish larvae locomotion analysis across experimental setups. Its flexibility, achieved with a Transformer neural network, allows the classification of actions regardless of tracking methods or frame rates. We demonstrate Megabouts ability to quantify sensorimotor transformations and enhance sensitivity to drug-induced phenotypes through high-throughput, high-resolution behavioral analysis.

animal behavior and cognition↗

bioRxiv2022

The Adaptor Protein 2 (AP2) complex modulates habituation and behavioral selection across multiple pathways and time windows

Animals constantly perceive and integrate information across sensory modalities, and their nervous systems must select behavioral responses appropriate to the current situation and prior experience. Genetic factors supporting this behavioral flexibility are often disrupted in neuropsychiatric conditions, and our previous work revealed the disease-associated ap2s1 gene critically supports habituation learning in acoustically-evoked escape behavior of zebrafish. ap2s1 encodes a subunit of the AP2 endocytosis adaptor complex and has been linked to autism spectrum disorder, though its mechanism and direct behavioral importance have not been established. Here, we show that multiple subunits of the AP2 complex regulate acoustically-evoked behavior selection and habituation learning. Furthermore, ap2s1 biases the choice between distinct escape behaviors in sensory modality-specific manners, and more broadly regulates action selection across different sensory contexts. Using tissue-specific and inducible transgenic rescue, we demonstrate that the AP2 complex functions acutely and in the nervous system to modulate acoustically-evoked habituation learning, suggesting several spatially and/or temporally distinct mechanisms through which AP2 regulates different aspects of escape behavior selection and performance. Altogether, we demonstrate that the AP2 complex coordinates action selection across stimulus modalities and contexts, providing a new vertebrate model for the role of ap2s1 in human conditions including autism spectrum disorder. SIGNIFICANCE STATEMENTThe AP2S1 gene has been linked to learning disabilities and autism spectrum disorders (ASD), though the mechanisms underlying its impact on human behavior are unknown. We explored how, when, and where this gene regulates vertebrate behavior, developing a zebrafish model to identify the roles and mechanisms through which ap2s1 modulates behavior. We find that ap2s1 regulates simple acoustically-evoked learning, as well as how individuals bias behavioral choice in a wide variety of contexts. We show that ap2s1 acts at multiple distinct time periods and locations both within and outside of neuronal tissues, revealing the diverse mechanisms and pathways through which it modulates vertebrate behavior.

neuroscience↗

bioRxiv2020

Early-life social experience shapes social avoidance reactions in larval zebrafish

Social experiences greatly define successive social behavior. Lack of such experiences, especially during critical phases of development, can severely impede the ability to behave adequately in social contexts. To date it is not well characterized how early-life social isolation leads to social deficits and impacts development. In many model species, it is challenging to fully control social experiences, because they depend on parental care. Moreover, complex social behaviors involve multiple sensory modalities, contexts, and actions. Hence, when studying social isolation effects, it is particularly important to parse apart social deficits from general developmental effects, such as abnormal motor learning. Here, we characterized how social experiences during early development of zebrafish larvae modulate their social behavior, at one week of age, when social avoidance reactions can be measured as discrete swim events. We show that raising larvae in social isolation leads to enhanced social avoidance, in terms of reaction distance and reaction strength. Specifically, larvae raised in isolation use a high-acceleration escape swim bout, the short latency C-start, more frequently during social interactions. These behavioral differences are absent in non-social contexts. By ablating the lateral line and presenting the fish with local water vibrations, we show that lateral line inputs are both necessary and sufficient to drive enhanced social avoidance reactions. Taken together, our results show that social experience during development is a critical factor in shaping mechanosensory avoidance reactions in larval zebrafish. HighlightsO_LILarval zebrafish raised in isolation show enhanced social avoidance reactions C_LIO_LIEnhanced avoidance is composed of increased avoidance distances and usage of high acceleration escape swims C_LIO_LIThe lateral line sensory organ is necessary and sufficient for the increased usage of high acceleration escape swims C_LI

neuroscience↗

bioRxiv2017

Clusterdv, a simple density-based clustering method that is robust, general and automatic.

How to partition a data set into a set of distinct clusters is a ubiquitous and challenging problem. The fact that data sets vary widely in features such as cluster shape, cluster number, density distribution, background noise, outliers and degree of overlap, makes it difficult to find a single algorithm that can be broadly applied. One recent method, based on search of density peaks, can be applied successfully to cluster many kinds of data, but it is not fully automatic, and fails on some simple data distributions. We propose an alternative approach, which estimates density dips between points, and allows robust determination of cluster number and distribution across a wide array of data, without any manual parameter adjustment. We show that this method is able to solve a range of synthetic and experimental data sets, where the underlying structure is known, and identifies consistent and meaningful clusters in new behavioural data.\n\nSignificanceIt is common that natural phenomena produce groupings, or clusters, in data, that can reveal the underlying processes. However, the form of these clusters can vary arbitrarily, making it challenging to find a single algorithm that identifies their structure correctly, without prior knowledge of the number of groupings or their distribution. We describe a simple clustering algorithm that is fully automatic and is able to correctly identify the number and shape of groupings in data of many types. We expect this algorithm to be useful in finding unknown natural phenomena present in data from a wide range of scientific fields.

bioinformatics↗