Biology subjects

Garcia, S.

Publications and source records attributed to Garcia, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2021

Tau modulates mRNA transcription, alternative polyadenylation profiles of hnRNPs, chromatin remodeling and spliceosome complexes

Tau protein is a known contributor in several neurodegenerative diseases, including Alzheimer s disease (AD) and frontotemporal dementia (FTD). It is well-established that tau forms pathological aggregates and fibrils in these diseases. Tau has been observed within the nuclei of neurons, but there is a gap in understanding regarding the mechanism by which tau modulates transcription. We are interested in the P301L mutation of tau, which has been associated with FTD and increased tau aggregation. Our study utilized tau-inducible HEK (iHEK) cells to reveal that WT and P301L tau distinctively alter the transcription and alternative polyadenylation (APA) profiles of numerous nuclear precursors mRNAs, which then translate to form proteins involved in chromatin remodeling and splicing. We isolated total mRNA before and after over-expressing tau and then performed Poly(A)-ClickSeq (PAC-Seq) to characterize mRNA expression and APA profiles. We characterized changes in Gene Ontology (GO) pathways using EnrichR and Gene Set Enrichment Analysis (GSEA). We observed that P301L tau up-regulates genes associated with reactive oxygen species responsiveness as well as genes involved in dendrite, microtubule, and nuclear body/speckle formation. The number of genes regulated by WT tau is greater than the mutant form, which indicates that the P301L mutation causes loss-of-function at the transcriptional level. WT tau up-regulates genes contributing to cytoskeleton-dependent intracellular transport, microglial activation, microtubule and nuclear chromatin organization, formation of nuclear bodies and speckles. Interestingly, both WT and P301L tau commonly down-regulate genes responsible for ubiquitin-proteosome system. In addition, WT tau significantly down-regulates several genes implicated in chromatin remodeling and nucleosome organization. Although there are limitations inherent to the model systems used, this study will improve understanding regarding the nuclear impact of tau at the transcriptional and post-transcriptional level. This study also illustrates the potential impact of P301L tau on the human brain genome during early phases of pathogenesis. Author summaryWhile tau biology has been extensively studied and closely linked to several neurodegenerative diseases, our current understanding of taus functions in the nucleus is limited. Given the role of tau in disease progression and pathogenesis, elucidating the function of tau activity in transcription and its nuclear accumulation may reveal novel therapeutic targets; therefore, helping identify new upstream pathways that have yet to be investigated. In this study, we used tau-inducible cell lines to uncover new molecular mechanisms by which tau functions in the nucleus. This study systematically investigates the changes in transcriptomic and alternative polyadenylation profiles modulated by WT and mutant P301L tau protein. In this manuscript, we report following new findings (i) tau modulates gene expression of transcripts associated with chromatin remodeling and splicing complexes; (ii) WT and mutant P301L tau regulate, differentially, transcription and alternative polyadenylation (APA) profiles; and (iii) P301L mutation affects the transcription mediated by tau protein. The potential role of tau in mediating transcription and alternative polyadenylation processes is not well studied, representing a novelty in the field. Therefore, this research establishes a new direction for investigating tau nuclear function in both human and mouse brains.

neuroscience↗

bioRxiv2021

Genome-wide analysis of long terminal repeat retrotransposons from the cranberry Vaccinium macrocarpon

BACKGROUNDLong terminal repeat (LTR) retrotransposons are widespread in plant genomes and play a large role in the generation of genomic variation. Despite this, their identification and characterization remains challenging, especially for non-model genomes. Hence, LTR retrotransposons remain undercharacterized in Vaccinium genomes, although they may be beneficial for current berry breeding efforts. OBJECTIVEExemplarily focusing on the genome of American cranberry (Vaccinium macrocarpon Aiton), we aim to generate an overview of the LTR retrotransposon landscape, highlighting the abundance, transcriptional activity, sequence, and structure of the major retrotransposon lineages. METHODSGraph-based clustering of whole genome shotgun Illumina reads was performed to identify the most abundant LTR retrotransposons and to reconstruct representative in silico full-length elements. To generate insights into the LTR retrotransposon diversity in V. macrocarpon, we also queried the genome assembly for presence of reverse transcriptases (RTs), the key domain of LTR retrotransposons. Using transcriptomic data, transcriptional activity of retrotransposons corresponding to the consensuses was analyzed. RESULTSWe provide an in-depth characterization of the LTR retrotransposon landscape in the V. macrocarpon genome. Based on 475 RTs harvested from the genome assembly, we detect a high retrotransposon variety, with all major lineages present. To better understand their structural hallmarks, we reconstructed 26 Ty1-copia and 28 Ty3-gypsy in silico consensuses that capture the detected diversity. Accordingly, we frequently identify association with tandemly repeated motifs, extra open reading frames, and specialized, lineage-typical domains. Based on the overall high genomic abundance and transcriptional activity, we suggest that retrotransposons of the Ale and Athila lineages are most promising to monitor retrotransposon-derived polymorphisms across accessions. CONCLUSIONSWe conclude that LTR retrotransposons are major components of the V. macrocarpon genome. The representative consensuses provide an entry point for further Vaccinium genome analyses and may be applied to derive molecular markers for enhancing cranberry selection and breeding.

plant biology↗

bioRxiv2021

Computational Design and Analysis of Modular Cells for Large Libraries of Exchangeable Product Synthesis Modules

Microbial metabolism can be harnessed to produce a large library of useful chemicals from renewable resources such as plant biomass. However, it is laborious and expensive to create microbial biocatalysts to produce each new product. To tackle this challenge, we have recently developed modular cell (ModCell) design principles that enable rapid generation of production strains by assembling a modular (chassis) cell with exchangeable production modules to achieve overproduction of target molecules. Previous computational ModCell design methods are limited to analyze small libraries of around 20 products. In this study, we developed a new computational method, named ModCell-HPC, capable of designing modular cells for large libraries with hundredths of products with a highly-parallel and multi-objective evolutionary algorithm. We demonstrated ModCell-HPC to design Escherichia coli modular cells towards a library of 161 endogenous production modules. From these simulations, we identified E. coli modular cells with few genetic manipulations that can produce dozens of molecules in a growth-coupled manner under different carbons sources. These designs revealed key genetic manipulations at the chassis and module levels to accomplish versatile modular cells. Furthermore, we used ModCell-HPC to identify design features that allow an existing modular cell to be re-purposed towards production of new molecules. Overall, ModCell-HPC is a useful tool towards more efficient and generalizable design of modular cells to help reduce research and development cost in biocatalysis.

synthetic biology↗

bioRxiv2021

Loss of Muscleblind Splicing Factor Shortens C. elegans Lifespan by Reducing the Activity of p38 MAPK/PMK-1 and Transcription Factors ATF-7 and Nrf/SKN-1

Muscleblind-like splicing regulators (MBNLs) are alternative splicing factors that have an important role in developmental processes. Dysfunction of these factors is a key contributor of different neuromuscular degenerative disorders, including Myotonic Dystrophy type 1 (DM1). Since DM1 is a multisystemic disease characterized by symptoms resembling accelerated aging, we asked whether MBNLs regulate cellular processes required to maintain normal lifespan. By utilizing the model organism Caenorhabditis elegans, we found that loss of MBL-1 (the sole ortholog of mammalian MBNLs), which is known to be required for normal lifespan, shortens lifespan by decreasing the activity of p38 MAPK/PMK-1 as well as the function of transcription factors ATF-7 and SKN-1. Furthermore, we show that mitochondrial stress caused by knockdown of mitochondrial electron transport chain components promotes the longevity of mbl-1 mutants in a partially PMK-1-dependent manner. Together, the data establish a mechanism of how DM1-associated loss of muscleblind affects lifespan. Furthermore, this study suggests that mitochondrial stress could alleviate symptoms caused by the dysfunction of muscleblind splicing factor, creating a potential approach to investigate for therapy. Reviewer token for the RNA-seq data (GEO: GSE146801): wvataksittaffcj

genetics↗

bioRxiv2020

Respiration and brain neural dynamics associated with interval timing during odor fear learning in rats

In fear conditioning, where a conditioned stimulus predicts the arrival of an aversive stimulus, the animal encodes the time interval between the two stimuli. Freezing, the most used index to assess learned fear, lacks the temporal resolution required to investigate interval timing at the early stages of learning. Here we monitored respiration to visualize anticipatory behavioral responses in an odor fear conditioning in rats, while recording theta (5-15Hz) and gamma (40-80Hz) brain oscillatory activities in the medial prefrontal cortex (mPFC), basolateral amygdala (BLA), dorsomedial striatum (DMS) and olfactory piriform cortex (PIR). We investigated the temporal patterns of respiration frequency and of theta and gamma activity power during the odor-shock interval. We found that akin to respiration patterns, theta temporal curves were modulated by the duration of the odor-shock interval in the four recording sites, and respected scalar property in mPFC and DMS. In contrast, gamma temporal curves were modulated by the interval duration only in the mPFC, and in a manner that did not respect scalar property. This suggests a preferential role for theta rhythm in interval timing. In addition, our data bring the novel idea that the respiratory rhythm might take part in the setting of theta activity dynamics.

neuroscience↗

bioRxiv2020

The deep and slow breathing characterizing rest favors brain respiratory-drive

A respiration-locked activity in the olfactory brain, mainly originating in the mechano-sensitivity of olfactory sensory neurons to air pressure, propagates from the olfactory bulb to the rest of the brain. Interestingly, changes in nasal airflow rate result in reorganization of olfactory bulb response. Therefore, if the respiratory drive of the brain originates in nasal airflow movements, then it should vary with respiration dynamics that occur spontaneously during natural conditions. We took advantage of the spontaneous variations of respiration dynamics during the different waking and sleep states to explore respiratory drive in various brain regions. We analyzed their local field potential activity relative to respiratory signal. We showed that respiration regime was state-specific, and that quiet waking was the only vigilance state during which all the recorded structures can be respiration-driven whatever the respiration frequency. We used a CO2-enriched air to change the respiratory regime associated to each state and, using a respiratory cycle-by-cycle analysis, we evidenced that the large and strong brain entrainment during quiet waking was the consequence of its associated respiration regime consisting in an optimal trade-off between deepness and duration of inspiration. These results show for the first time that changes in respiration regime alter the cortical dynamics and that the respiratory regime associated with rest is optimal for respiration to drive the brain.

neuroscience↗

bioRxiv2020

CoExp Web, a web tool for the exploitation of co-expression networks

SummaryThis paper presents the CoExp Web tool. CoExp is a software tool and a Web resource that fosters research on co-expression network models by providing a highly usable means to exploit and share multiple network models. Availability and Implementationthe Web resource is accessible at https://snca.atica.um.es/coexp/. The software at the front and back-ends is accessible at https://github.com/SoniaRuiz/CoExp_Web. Contactskgtsg0@ucl.ac.uk (Sonia Garcia-Ruiz)

bioinformatics↗

bioRxiv2020

Development of a genome-scale metabolic model of Clostridium thermocellum and its applications for integration of multi-omics datasets and strain design

Solving environmental and social challenges such as climate change requires a shift from our current non-renewable manufacturing model to a sustainable bioeconomy. To lower carbon emissions in the production of fuels and chemicals, plant biomass feedstocks can replace petroleum using microorganisms as catalysts. The anaerobic thermophile Clostridium thermocellum is a promising bacterium for bioconversion due to its capability to efficiently degrade untreated lignocellulosic biomass. However, the complex metabolism of C. thermocellum is not fully understood, hindering metabolic engineering to achieve high titers, rates, and yields of targeted molecules. In this study, we developed an updated genome-scale metabolic model of C. thermocellum that accounts for recent metabolic findings, has improved prediction accuracy, and is standard-conformant to ensure easy reproducibility. We illustrated two applications of the developed model. We first formulated a multi-omics integration protocol and used it to understand redox metabolism and potential bottlenecks in biofuel (e.g., ethanol) production in C. thermocellum. Second, we used the metabolic model to design modular cells for efficient production of alcohols and esters with broad applications as flavors, fragrances, solvents, and fuels. The proposed designs not only feature intuitive push-and-pull metabolic engineering strategies, but also novel manipulations around important central metabolic branch-points. We anticipate the developed genome-scale metabolic model will provide a useful tool for system analysis of C. thermocellum metabolism to fundamentally understand its physiology and guide metabolic engineering strategies to rapidly generate modular production strains for effective biosynthesis of biofuels and biochemicals from lignocellulosic biomass.

systems biology↗

bioRxiv2020

Establishment of a pancreatic adenocarcinoma molecular gradient (PAMG) that predicts the clinical outcome of pancreatic cancer

BACKGROUNDA significant gap in pancreatic ductal adenocarcinoma (PDAC) patients care is the lack of molecular parameters characterizing tumors and allowing a personalized treatment. The goal of this study was to examine whole PDAC transcriptomic profiles to define a signature that would predict aggressiveness and treatment responsiveness better than done until now. METHODS AND PATIENTSTumors were obtained from 76 consecutive resectable (n=40) or unresectable (n=36) tumors. PDAC were transplanted in mice to produce patient-drived xenografts (PDX). PDX were classified according to their histology into five groups, from highly undifferentiated to well differentiated. This classification resulted strongly associated with tumors aggressiveness. A PDAC molecular gradient (PAMG) was constructed from PDX transcriptomes recapitulating the five histological groups along a continuous gradient. The prognostic and predictive value for PMAG was evaluated in: i/ two independent series (n=598) of resected tumors; ii/ 60 advanced tumors obtained by diagnostic EUS-guided biopsy needle flushing and iii/ on 28 biopsies from mFOLFIRINOX treated metastatic tumors. RESULTSA unique transcriptomic signature (PAGM) was generated with significant and independent prognostic value. PAMG significantly improves the characterization of PDAC heterogeneity compared to non-overlapping classifications as validated in 4 independent series of tumors (e.g. 308 consecutive resected PDAC, HR=0.321 95% CI [0.207;0.5] and 60 locally-advanced or metastatic PDAC, HR=0.308 95% CI [0.113;0.836]). The PAMG signature is also associated with progression under mFOLFIRINOX treatment (Pearson correlation to tumor response: -0.67, p-value < 0.001). CONCLUSIONWe identified a transcriptomic signature (PAMG) that, unlike all other stratification schemas already proposed, classifies PDAC along a continuous gradient. It can be performed on formalin-fixed paraffin-embedded samples and EUS-guided biopsies showing a strong prognostic value and predicting mFOLFIRINOX responsiveness. We think that PAMG could unify all PDAC preexisting classifications inducing a shift in the actual paradigm of binary classifications towards a better characterization in a gradient. Trial RegistrationThe PaCaOmics study is registered at www.clinicaltrials.gov with registration number NCT01692873. The validation BACAP study is registered at www.clinicaltrials.gov with registration number NCT02818829.

cancer biology↗

bioRxiv2020

Human-like telomeres in Zostera marina reveal a mode of transition from the plant to the human telomeric sequences

A previous study describing the genome of Zostera marina, the most widespread seagrass in the Northern hemisphere, revealed some genomic signatures of adaptation to the aquatic environment. Important features related to the back-to-the-sea reverse evolutionary pathway were found, such as the loss of stomatal genes, while other functions like an algal-like cell wall composition were acquired. Beyond these, the genome structure and organization were comparable to the majority of plant genomes sequenced, except for one striking feature that went unnoticed at that time: the presence of human-like instead of the expected plant-type telomeric sequences. By using different experimental approaches including FISH, NGS and Ba131 analysis, we have confirmed its telomeric location in the chromosomes of Z. marina. We have also identified its telomerase RNA subunit (TR), confirming the presence of the human-type telomeric sequence in the template region. Remarkably, this region was found to be very variable even in clades with a highly conserved telomeric sequence across their species. Based on this observation, we propose that alternative annealing preferences in the template borders can explain the transition between the plant and human telomeric sequences. The further identification of paralogues of TR in several plant genomes brought us to the hypothesis that plants may keep an increased ability to change their telomeric sequence. We discuss the implications of this occurrence in the evolution of telomeres while introducing a mechanistic model for the transition from the plant to the human telomeric sequences.

evolutionary biology↗

bioRxiv2020

SpikeForest: reproducible web-facing ground-truth validation of automated neural spike sorters

Spike sorting is a crucial but time-intensive step in electrophysiological studies of neuronal activity. While there are many popular software packages for spike sorting, there is little consensus about which are the most accurate under different experimental conditions. SpikeForest is an open-source and reproducible software suite that benchmarks the performance of automated spike sorting algorithms across an extensive, curated database of electrophysiological recordings with ground truth, displaying results interactively on a continuously-updating website. With contributions from over a dozen participating laboratories, our database currently comprises 650 recordings (1.3 TB total size) with around 35,000 ground-truth units. These data include extracellular recordings paired with intracellular voltages, state-of-the-art simulated recordings, and hybrid synthetic datasets. Ten of the most frequently used modern spike sorting codes are wrapped under a common Python framework and evaluated on a compute cluster using an automated pipeline. SpikeForest validates and documents community progress in automated spike sorting, and guides neuroscientists to an optimal choice of sorter and parameters for a wide range of probes and brain regions.

neuroscience↗

bioRxiv2019

SpikeInterface, a unified framework for spike sorting

Much development has been directed towards improving the performance and automation of spike sorting. This continuous development, while essential, has contributed to an over-saturation of new, incompatible tools that hinders rigorous benchmarking and complicates reproducible analysis. To address these limitations, we developed SpikeInterface, a Python framework designed to unify preexisting spike sorting technologies into a single codebase and to facilitate straightforward comparison and adoption of different approaches. With a few lines of code, researchers can reproducibly run, compare, and benchmark most modern spike sorting algorithms; pre-process, post-process, and visualize extracellular datasets; validate, curate, and export sorting outputs; and more. In this paper, we provide an overview of SpikeInterface and, with applications to real and simulated datasets, demonstrate how it can be utilized to reduce the burden of manual curation and to more comprehensively benchmark automated spike sorters.

neuroscience↗

bioRxiv2019

Understanding and eliminating the detrimental effect of endogenous thiamine auxotrophy on metabolism of the oleaginous yeast Yarrowia lipolytica

Thiamine is an essential vitamin that functions as a cofactor for key enzymes in carbon and energy metabolism for all living cells. While most plants, fungi and bacteria can synthesize thiamine de novo, the oleaginous yeast, Yarrowia lipolytica, cannot. In this study, we used proteomics together with physiological characterization to understand key metabolic processes influenced and regulated by thiamine availability and identified the genetic basis of thiamine auxotrophy in Y. lipolytica. Specifically, we found thiamine depletion results in decreased protein abundance of the lipid biosynthesis pathways and energy metabolism (i.e., ATP synthase), attributing to the negligible growth and poor sugar assimilation observed in our study. Using comparative genomics, we identified the missing gene scTHI13, encoding the 4-amino-5-hydroxymethyl-2-methylpyrimidine phosphate synthase for the de novo thiamine synthesis in Y. lipolytica, and discovered an exceptional promoter, P3, that exhibits strong activation or tight repression by low and high thiamine concentrations, respectively. Capitalizing on the strength of our thiamine-regulated promoter (P3) to express the missing gene, we engineered the first thiamine-prototrophic Y. lipolytica reported to date. By comparing this engineered strain to the wildtype, we unveiled the tight relationship linking thiamine availability to lipid biosynthesis and demonstrated enhanced lipid production with thiamine supplementation in the engineered thiamine-prototrophic Y. lipolytica.\n\nIMPORTANCEThiamine plays a crucial role as an essential cofactor for enzymes in carbon and energy metabolism of all living cells. Thiamine deficiency has detrimental consequences on cellular health. Yarrowia lipolytica, a non-conventional oleaginous yeast with broad biotechnological applications, is a native thiamine auxotroph, whose effects on cellular metabolism are not well understood. Therefore, Y. lipolytica is an ideal eukaryotic host to study thiamine metabolism, especially as mammalian cells are also thiamine-auxotrophic and thiamine deficiency is implicated in several human diseases. This study elucidates the fundamentals of thiamine deficiency on cellular metabolism of Y. lipolytica and identifies genes and novel thiamine-regulated elements that eliminate thiamine auxotrophy in Y. lipolytica. Furthermore, discovery of thiamine-regulated elements enables development of thiamine biosensors with useful applications in synthetic biology and metabolic engineering.

microbiology↗

bioRxiv2019

Single mutation at a highly conserved region of chloramphenicol acetyltransferase enables thermophilic isobutyl acetate production directly from cellulose by Clostridium thermocellum

BackgroundEsters are versatile chemicals and potential drop-in biofuels. To develop a sustainable production platform, microbial ester biosynthesis using alcohol acetyltransferases (AATs) has been studied for decades. Volatility of esters endows thermophilic production with advantageous downstream product separation. However, due to the limited thermal stability of AATs known, the ester biosynthesis has largely relied on use of mesophilic microbes. Therefore, developing thermostable AATs is important for thermophilic ester production directly from lignocellulosic biomass by the thermophilic consolidated bioprocessing (CBP) microbes, e.g., Clostridium thermocellum.\n\nResultsIn this study, we engineered a thermostable chloramphenicol acetyltransferase from Staphylococcus aureus (CATSa) for enhanced isobutyl acetate production at elevated temperature. We first analyzed the broad alcohol substrate range of CATSa. Then, we targeted a highly conserved region in the binding pocket of CATSa for mutagenesis. The mutagenesis revealed that F97W significantly increased conversion of isobutanol to isobutyl acetate. Using CATSa F97W, we demonstrated the engineered C. thermocellum could produce isobutyl acetate directly from cellulose.\n\nConclusionsThis study highlights that CAT is a potential thermostable AAT that can be harnessed to develop the thermophilic CBP microbial platform for biosynthesis of designer bioesters directly from lignocellulosic biomass.

synthetic biology↗

bioRxiv2019

The effect of sample size on polygenic hazard models for prostate cancer

We aimed to determine the effect of sample size on performance of polygenic hazard score (PHS) models in predicting the age at onset of prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training (34,444 samples) and testing (6,417 samples) sets. Two PHS model-building strategies were investigated. Established-SNP model considered 65 SNPs that had been associated with prostate cancer in the literature. A stepwise SNP selection was used to develop Discovery-SNP models. The performance of each PHS model was calculated for random sizes of the training set (1 to 30 thousand). The performance of a representative Established-SNP model was estimated for random sizes of the testing set (0.5 to 6 thousand). Mean HR98/50 (hazard ratio of top 2% to the average in the test set) of the Established-SNP model increased from 1.73[95%CI: 1.69-1.77] to 2.41[2.40-2.43] when the number of training samples was increased from 1 to 30 thousand. The corresponding HR98/50 of the Discovery-SNP model increased from 1.05[0.93-1.18] to 2.19[2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 and 6 thousand observations were 1.78[1.70-1.85] and 1.73[1.71-1.76], respectively. We estimate that a study population of 20 to 30 thousand men is required to develop Discovery-SNP PHS models for prostate cancer. The required sample size could be reduced to 10 thousand samples, if a set of SNPs associated with the disease has already been established.\n\nAuthor summaryPolygenic hazard scores represent a recent advancement in polygenic prediction to model the age of onset of various diseases, such as Alzheimers disease or prostate cancer. These scores accumulate small effect sizes from several tens of genetic variants and can be used to establish an individuals risk of experiencing an event relative to a control population across time. The largest barrier to the development of polygenic hazard scores is the large number of study subjects needed to develop the underlying models. We sought to understand the effect of varying the total number of samples on the performance of a polygenic hazard score in the context of prostate cancer. We found that the performance of the score did not appreciably change beyond 20 to 30 thousand observations when developing the model from scratch. However, when the discovery of the genetic variants can be borrowed from those already identified in the literature to be associated with the disease, the required number of samples is reduced to 10 thousand with no appreciable detriment in performance. We hope that these results can guide the design of future studies of polygenic scores in other diseases and demonstrate the importance of genome-wide association studies.

genetics↗

bioRxiv2019

Reconstructing Phylogenetic Relationships Based On Repeat Sequence Similarities

A recent phylogenetic method based on genome-wide abundance of different repeat types proved to be useful in reconstructing the evolutionary history of several plant and animal groups. Here, we demonstrate that an alternative information source from the repeatome can also be employed to infer phylogenetic relationships among taxa. Specifically, this novel approach makes use of the repeat sequence similarity matrices obtained from the comparative clustering analyses of RepeatExplorer 2, which are subsequently transformed to between-taxa distance matrices. These pairwise matrices are used to construct neighbour-joining trees for each of the top most-abundant clusters and they are finally summarized in a consensus network. This methodology was tested on three groups of angiosperms and one group of insects, resulting in congruent evolutionary hypotheses compared to more standard systematic analyses based on commonly used DNA markers. We propose that the combined application of these phylogenetic approaches based on repeat abundances and repeat sequence similarities could be helpful to understand mechanisms governing genome and repeatome evolution.

evolutionary biology↗

bioRxiv2019

Comparison of Multi-objective Evolutionary Algorithms to Solve the Modular Cell Design Problem for Novel Biocatalysis

A large space of chemicals with broad industrial and consumer applications could be synthesized by engineered microbial biocatalysts. However, the current strain optimization process is prohibitively laborious and costly to produce one target chemical and often requires new engineering efforts to produce new molecules. To tackle this challenge, modular cell design based on a chassis strain that can be combined with different product synthesis pathway modules has been recently proposed. This approach seeks to minimize unexpected failure and avoid task repetition, leading to a more robust and faster strain engineering process. The modular cell design problem was mathematically formulated using a multi-objective optimization framework.[1] In this study, we evaluated a library of the state-of-the-art multi-objective evolutionary algorithms (MOEAs) to identify the most effective method to solve the modular cell design problem. Using the best MOEA, we found better solutions for modular cells compatible with many product synthesis modules. Furthermore, the best performing algorithm could provide better and more diverse design options that might help increase the likelihood of successful experimental implementation. We identified key parameter configurations to overcome the difficulty associated with multi-objective optimization problems with many competing design objectives. Interestingly, we found that MOEA performance with a real application problem, e.g., the modular strain design problem, does not always correlate with artificial benchmarks. Overall, MOEAs provide powerful tools to solve the modular cell design problem for novel biocatalysis.

synthetic biology↗

bioRxiv2018

New insights from 22-kHz ultrasonic vocalizations to characterize fear responses: relationship with respiration and brain oscillatory dynamics

Fear behavior depends on interactions between the medial prefrontal cortex (mPFC) and the basolateral amygdala (BLA), and the expression of fear involves synchronized activity in theta and gamma oscillatory activities. In addition, freezing, the most classical measure of fear response in rodents, temporally coincides with the development of sustained 4-Hz oscillations in prefrontal- amygdala circuits. Interestingly, these oscillations were recently shown to depend on the animals respiratory rhythm, supporting the growing body of evidence pinpointing the influence of nasal breathing on brain rhythms. During fearful states, rats also emit 22-kHz ultrasonic vocalizations (USV) which drastically affect respiratory rhythm. However, the relationship between 22-kHz USV, respiration and brain oscillatory activities is still unknown. Yet such information is crucial for a comprehensive understanding of how the different components of fear response collectively modulate rats brain neural dynamics. Here we trained male rats in an odor fear conditioning task, while recording simultaneously local field potentials in BLA, mPFC and olfactory piriform cortex, together with USV calls and respiration. We show that USV calls coincide with an increase in delta and gamma power and a decrease in theta power. In addition, during USV emission in contrast to silent freezing, there is no coupling between respiratory rate and delta frequency, and the modulation of fast oscillations amplitude relative to the phase of respiration is modified. We propose that sequences of USV calls could result in a differential gating of information within the network of structures sustaining fear behavior, thus potentially modulating fear expression/memory.\n\nSignificance StatementWhile freezing is the most frequently used measure of fear, it is only one amongst the different components of rodents response to threatening events. USV is another index that gives additional insight into the socioemotional status of an individual. Our study is the first to describe the effects of USV production on rats brain oscillatory activities in the fear neural network, and to relate some of them to changes in nasal breathing. A better knowledge of the impact of USV calls on brain neural dynamics is not only important for understanding the respective weight of the different components of fear response, but is also particularly relevant for rodent models of human neuropsychiatric disorders, for which socio-affective communication is severely impaired.

neuroscience↗