Tying the knot: Unraveling the intricacies of the coronavirus frameshift pseudoknot
by Luke Trinity, Ulrike Stege, Hosna Jabbari
Understanding and targeting functional RNA structures towards treatment of coronavirus infection can help us to prepare for novel variants of SARS-CoV-2 (the virus causing COVID-19), and any other coronaviruses that could emerge via human-to-human transmission or potential zoonotic (inter-species) events. Leveraging the fact that all coronaviruses use a mechanism known as −1 programmed ribosomal frameshifting (−1 PRF) to replicate, we apply algorithms to predict the most energetically favourable secondary structures (each nucleotide involved in at most one pairing) that may...
Source: PLoS Computational Biology - May 7, 2024 Category: Biology Authors: Luke Trinity Source Type: research
Group-selection via aggregative propagule-formation enables cooperative multicellularity in an individual based, spatial model
by Istv án Oszoli, István Zachar
The emergence of multicellularity is one of the major transitions in evolution that happened multiple times independently. During aggregative multicellularity, genetically potentially unrelated lineages cooperate to form transient multicellular groups. Unlike clonal multicellularity, aggregative multicellular organisms do not rely on kin selection instead other mechanisms maintain cooperation against cheater phenotypes that benefit from cooperators but do not contribute to groups. Spatiality with limited diffusion can facilitate group selection, as interactions among individuals are rest...
Source: PLoS Computational Biology - May 7, 2024 Category: Biology Authors: Istv án Oszoli Source Type: research
Challenges of COVID-19 Case Forecasting in the US, 2020 –2021
by Velma K. Lopez, Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O ’Dea, Madeline Adee, Turgay Ayer, Jagpreet Chhatwal, Ozden O. Dalgic, Mary A. Ladd, Benjamin P. Linas, Peter P. Mueller, Jade Xiao, Johannes Bracher, Alvaro J. Castro Rivadeneira, Aaron Gerding, Tilmann Gneiting, Yuxin Huang, Dasuni Jayawardena, Abdul H. Kanji, Khoa Le, Anja Mühlemann, Jarad Niem i, Evan L. Ray, Ariane Stark, Yijin Wang, Nutcha Wattanachit, Martha W. Zorn, Sen Pei, Jeffrey Shaman, Teresa K. Yamana, Samuel R. Tarasewicz, Daniel J. Wilson, Sid Baccam, Heidi Gurung, Steve Stage, Brad Suchoski, Lei Gao, Zhiling Gu, Myungjin Kim, Xi...
Source: PLoS Computational Biology - May 6, 2024 Category: Biology Authors: Velma K. Lopez Source Type: research
MGSurvE: A framework to optimize trap placement for genetic surveillance of mosquito populations
by H éctor M. Sánchez C., David L. Smith, John M. Marshall
Genetic surveillance of mosquito populations is becoming increasingly relevant as genetics-based mosquito control strategies advance from laboratory to field testing. Especially applicable are mosquito gene drive projects, the potential scale of which leads monitoring to be a significant cost driver. For these projects, monitoring will be required to detect unintended spread of gene drive mosquitoes beyond field sites, and the emergence of alternative alleles, such as drive-resistant alleles or non-functional effector genes, within intervention sites. This entai...
Source: PLoS Computational Biology - May 6, 2024 Category: Biology Authors: H éctor M. Sánchez C. Source Type: research
On the impact of re-mating and residual fertility on the Sterile Insect Technique efficacy: Case study with the medfly, < i > Ceratitis capitata < /i >
In this study, we consider single- and double-mated females. We first show that SIT can be successful only if the residual fertility is less than a threshold value that depends on the basic offspring number of the targeted pest population, the re-mating rates, and the parameters of double-mated females. Then, we show how the sterile male release rate is affected by the parameters of double-mated females and the male residual fertility. Different scenarios are explored with continuous and periodic sterile male releases, with and without ginger aromatherapy, which is known to enhance sterile male competitiveness, and also ta...
Source: PLoS Computational Biology - May 6, 2024 Category: Biology Authors: Yves Dumont Source Type: research
Removing direct photocurrent artifacts in optogenetic connectivity mapping data via constrained matrix factorization
by Benjamin Antin, Masato Sadahiro, Marta Gajowa, Marcus A. Triplett, Hillel Adesnik, Liam Paninski
Monosynaptic connectivity mapping is crucial for building circuit-level models of neural computation. Two-photon optogenetic stimulation, when combined with whole-cell recording, enables large-scale mapping of physiological circuit parameters. In this experimental setup, recorded postsynaptic currents are used to infer the presence and strength of connections. For many cell types, nearby connections are those we expect to be strongest. However, when the postsynaptic cell expresses opsin, optical excitation of nearby cells c...
Source: PLoS Computational Biology - May 6, 2024 Category: Biology Authors: Benjamin Antin Source Type: research
Brain2GAN: Feature-disentangled neural encoding and decoding of visual perception in the primate brain
by Thirza Dado, Paolo Papale, Antonio Lozano, Lynn Le, Feng Wang, Marcel van Gerven, Pieter Roelfsema, Ya ğmur Güçlütürk, Umut Güçlü
A challenging goal of neural coding is to characterize the neural representations underlying visual perception. To this end, multi-unit activity (MUA) of macaque visual cortex was recorded in a passive fixation task upon presentation of faces and natural images. We analyzed the relationship between MUA and latent representations of state-of-the-art deep generative models, including the conventional and feature-disentangled representations of generative adversarial networks (GANs) (i....
Source: PLoS Computational Biology - May 6, 2024 Category: Biology Authors: Thirza Dado Source Type: research
< i > Cooltools < /i > : Enabling high-resolution Hi-C analysis in Python
by Open2C , Nezar Abdennur, Sameer Abraham, Geoffrey Fudenberg, Ilya M. Flyamer, Aleksandra A. Galitsyna, Anton Goloborodko, Maxim Imakaev, Betul A. Oksuz, Sergey V. Venev, Yao Xiao
Chromosome conformation capture (3C) technologies reveal the incredible complexity of genome organization. Maps of increasing size, depth, and resolution are now used to probe genome architecture across cell states, types, and organisms. Larger datasets add challenges at each step of computational analysis, from storage and memory constraints to researchers ’ time; however, analysis tools that meet these increased resource demands have not k...
Source: PLoS Computational Biology - May 6, 2024 Category: Biology Authors: Open2C Source Type: research
Differential disruptions in population coding along the dorsal-ventral axis of CA1 in the APP/PS1 mouse model of A β pathology
by Udaysankar Chockanathan, Krishnan Padmanabhan
Alzheimer ’s Disease (AD) is characterized by a range of behavioral alterations, including memory loss and psychiatric symptoms. While there is evidence that molecular pathologies, such as amyloid beta (Aβ), contribute to AD, it remains unclear how this histopathology gives rise to such disparate behaviora l deficits. One hypothesis is that Aβ exerts differential effects on neuronal circuits across brain regions, depending on the neurophysiology and connectivity of different areas. To test this, we recorded from large neuronal populations in dorsal CA1 (dCA1) and ventra...
Source: PLoS Computational Biology - May 6, 2024 Category: Biology Authors: Udaysankar Chockanathan Source Type: research
Re-awakening the brain: Forcing transitions in disorders of consciousness by external < i > in silico < /i > perturbation
by Paulina Clara Dagnino, Anira Escrichs, Ane L ópez-González, Olivia Gosseries, Jitka Annen, Yonatan Sanz Perl, Morten L. Kringelbach, Steven Laureys, Gustavo Deco
A fundamental challenge in neuroscience is accurately defining brain states and predicting how and where to perturb the brain to force a transition. Here, we investigated resting-state fMRI data of patients suffering from disorders of consciousness (DoC) after coma (minimally conscious and unresponsive wakefulness states) and healthy controls. We applied model-free and model-based approaches to help elucidate the underlying brain mechanisms of patients with ...
Source: PLoS Computational Biology - May 3, 2024 Category: Biology Authors: Paulina Clara Dagnino Source Type: research
A systematic analysis of regression models for protein engineering
by Richard Michael, Jacob K æstel-Hansen, Peter Mørch Groth, Simon Bartels, Jesper Salomon, Pengfei Tian, Nikos S. Hatzakis, Wouter Boomsma
To optimize proteins for particular traits holds great promise for industrial and pharmaceutical purposes. Machine Learning is increasingly applied in this field topredict properties of proteins, thereby guiding the experimental optimization process. A natural question is: How much progress are we making with such predictions, and how important is the choice of regressor and representation? In this paper, we demonstrate that different assessment criteria for regressor performance ca...
Source: PLoS Computational Biology - May 3, 2024 Category: Biology Authors: Richard Michael Source Type: research
A mathematical model for the role of dopamine-D2 self-regulation in the production of ultradian rhythms
by An Qi Zhang, Martin R. Ralph, Adam R. Stinchcombe
Many self-motivated and goal-directed behaviours display highly flexible, approximately 4 hour ultradian (shorter than a day) oscillations. Despite lacking direct correspondence to physical cycles in the environment, these ultradian rhythms may be involved in optimizing functional interactions with the environment and reflect intrinsic neural dynamics. Current evidence supports a role of mesostriatal dopamine (DA) in the expression and propagation of ultradian rhythmicity, however, the biochemical processes underpinning these oscillations remain to be identified. Here, ...
Source: PLoS Computational Biology - May 3, 2024 Category: Biology Authors: An Qi Zhang Source Type: research
Visual social information use in collective foraging
by David Mezey, Dominik Deffner, Ralf H. J. M. Kurvers, Pawel Romanczuk
Collective dynamics emerge from individual-level decisions, yet we still poorly understand the link between individual-level decision-making processes and collective outcomes in realistic physical systems. Using collective foraging to study the key trade-off between personal and social information use, we present a mechanistic, spatially-explicit agent-based model that combines individual-level evidence accumulation of personal and (visual) social cues with particle-based movement. Under idealized conditions without physical constraints, our mechanist...
Source: PLoS Computational Biology - May 3, 2024 Category: Biology Authors: David Mezey Source Type: research
Machine-learning and mechanistic modeling of metastatic breast cancer after neoadjuvant treatment
by Sebastien Benzekry, Michalis Mastri, Chiara Nicol ò, John M. L. Ebos
Clinical trials involving systemic neoadjuvant treatments in breast cancer aim to shrink tumors before surgery while simultaneously allowing for controlled evaluation of biomarkers, toxicity, and suppression of distant (occult) metastatic disease. Yet neoadjuvant clinical trials are rarely preceded by preclinical testing involving neoadjuvant treatment, surgery, and post-surgery monitoring of the disease. Here we used a mouse model of spontaneous metastasis occurring after surgical removal of orthotopically implanted primary tumors to develop a predi...
Source: PLoS Computational Biology - May 3, 2024 Category: Biology Authors: Sebastien Benzekry Source Type: research
Epidemiological and health economic implications of symptom propagation in respiratory pathogens: A mathematical modelling investigation
ConclusionsOverall, the preferred intervention type depended on the combination of the strength of symptom propagation and uptake. Given the importance of determining robust public health responses, we highlight the need to gather further data on symptom propagation, with our modelling framework acting as a template for future analysis. (Source: PLoS Computational Biology)
Source: PLoS Computational Biology - May 3, 2024 Category: Biology Authors: Phoebe Asplin Source Type: research
