Biology subjects

Franco, M.

Publications and source records attributed to Franco, M..

33 records · Page 2Linked to original sources

bioRxiv2021

Mitochondrial mutational spectrum is associated with mammalian longevity: a novel signature of oxidative damage.

The mutational spectrum of the mitochondrial DNA (mtDNA) does not resemble any of the known mutational signatures of the nuclear genome and variation in mtDNA mutational spectra between different organisms is still incomprehensible. Since mitochondria is tightly involved in aerobic energy production, it is expected that mtDNA mutational spectra is affected by the oxidative damage. Assuming that oxidative damage increases with age, we analyze mtDNA mutagenesis of different species. Analysing (i) dozens thousands of somatic mtDNA mutations in samples of different age (ii) 70053 polymorphic synonymous mtDNA substitutions, reconstructed in 424 mammalian species with different generation length and (iii) synonymous nucleotide content of 650 complete mitochondrial genomes of mammalian species we observed that the frequency of AH>GH substitutions (H - heavy chain notation) is twice higher in species with high versus low generation length making their mtDNA more AH poor and GH rich. Considering that AH>GH substitutions are also sensitive to the time spent single stranded (TSSS) during asynchroniuos mtDNA replication we demonstrated that AH>GH substitution rate is a function of both species-specific generation length and position specific TSSS. We propose that AH>GH is a mitochondria-specific signature of oxidative damage associated with both aging and TSSS.

bioinformatics↗

bioRxiv2021

Nuclear DNA-encoded fragments of mitochondrial DNA (mtDNA) confound analysis of selection of mtDNA mutations in human primordial germ cells.

The resilience of the mitochondrial genome to a high mutational pressure depends, in part, on purifying selection against detrimental mutations in the germline. It is crucial to understand the mechanisms of this process. Recently, Floros et al. concluded that much of the purifying selection takes place during the proliferation of primordial germ cells (PGCs) because, according to their analysis, the synonymity of mutations in late PGCs was seemingly increased compared to those in early PGCs. We re-analyzed the Floros et al. mutational data and discovered a high proportion of sequence variants that are not true mutations, but originate from NUMTs, the latter of which are segments of mitochondrial DNA (mtDNA) inserted into nuclear DNA, up to millions of years ago. This is a well-known artifact in mtDNA mutational analysis. Removal of these artifacts from the Floros et al. dataset abolishes the reported effect of purifying selection in PGCs. We therefore conclude that the mechanism of germline selection of mtDNA mutations remains open for debate, and more research is needed to fully elucidate the timing and nature of this process.

genomics↗

bioRxiv2021

Range-wide habitat use and Key Biodiversity Area coverage for a lowland tropical forest raptor across an increasingly deforested landscape

Quantifying habitat use is important for understanding how animals meet their requirements for survival and provides useful information for conservation planning. Currently, assessments of range-wide habitat use that delimit species distributions are incomplete for many taxa. The harpy eagle (Harpia harpyja) is a raptor of conservation concern, widely distributed across Neotropical lowland forests, that currently faces threats from increasing habitat loss and fragmentation. Here, we use a logistic regression modelling framework to identify habitat resource selection and predict habitat suitability based on a new method developed from the International Union for the Conservation of Nature Area of Habitat range metric. From the habitat use model, we performed a gap analysis to identify areas of high habitat suitability in regions with limited coverage in the Key Biodiversity Area (KBA) network. Range-wide habitat use indicated that harpy eagles prefer areas of 70-75 % evergreen forest cover, low elevation, and high vegetation heterogeneity. Conversely, harpy eagles avoid areas of >10 % cultivated landcover and mosaic forest, and topographically complex areas. Our habitat use model identified a large continuous area across the pan-Amazonia region, and a habitat corridor from the Choco-Darien ecoregion of Colombia running north along the Caribbean coast of Central America. Little habitat was predicted across the Atlantic Forest biome, which is now severely degraded. The current KBA network covered [~]18 % of medium to high suitability harpy eagle habitat exceeding the target representation (10 %). Four major areas of high suitability habitat lacking coverage in the KBA network were identified in the Choco-Darien ecoregion of Colombia, western Guyana, and north-west Brazil. We recommend these multiple gaps of habitat as new KBAs for strengthening the current KBA network. Modelled area of habitat estimates as described here are a useful tool for large-scale conservation planning and can be readily applied to many taxa.

ecology↗

bioRxiv2021

Shotgun Immunoproteomic Approach for the Discovery of Linear B Cell Epitopes in Biothreat Agents Francisella tularensis and Burkholderia pseudomallei

Peptide-based subunit vaccines are coming to the forefront of current vaccine approaches, with safety and cost-effective production among their top advantages. Peptide vaccine formulations consist of multiple synthetic linear epitopes that together trigger desired immune responses that can result in robust immune memory. The advantages of peptide epitopes are their simple structure, ease of synthesis, and ability to stimulate immune responses by means that do not require complex 3D conformation. Identification of linear epitopes is currently an inefficient process that requires thorough characterization of previously identified full-length protein antigens, or laborious techniques involving genetic manipulation of organisms. In this study, we apply a newly developed generalizable screening method that enables efficient identification of B cell epitopes in the proteomes of pathogenic bacteria. As a test case, we used this method to identify epitopes in the proteome of Francisella tularensis (Ft), a Select Agent with a well-characterized immunoproteome. Our screen identified many peptides that map to known antigens, including verified and predicted outer membrane proteins and extracellular proteins, validating the utility of this approach. We then used the method to identify seroreactive peptides in the less characterized immunoproteome of Select Agent Burkholderia pseudomallei (Bp). This screen revealed known Bp antigens as well as proteins that have not been previously identified as antigens. The present workflow is easily adaptable to detecting peptide targets relevant to the immune systems of other mammalian species, including humans (depending upon the availability of convalescent sera from patients), and could aid in accelerating the discovery of B cell epitopes and development of vaccines to counter emerging biological threats.

immunology↗

bioRxiv2021

Bi-phasic dynamics of the mitochondrial DNA mutation m.3243A>G in blood: An unbiased, mutation level-dependent model implies positive selection in the germline.

The A-to-G point mutation at position 3243 in the human mitochondrial genome (m.3243A>G) is the most common pathogenic mtDNA variant responsible for disease in humans. It is widely accepted that m.3243A>G levels decrease in blood with age, and an age correction representing [~]2% annual decline is often applied to account for this change in mutation level. Here we report that recent data indicate the dynamics of m.3243A>G are more complex and depend on the mutation level in blood in a bi-phasic way. Consequently, the traditional 2% correction, which is adequate on average, creates opposite predictive biases at high and low mutation levels. Unbiased age correction is needed to circumvent these drawbacks of the standard model. We propose to eliminate both biases by using an approach where age correction depends on mutation level in a biphasic way to account for the dynamics of m.3243A>G in blood. The utility of this approach was further tested in estimating germline selection of m.3243A>G. The biphasic approach permitted us to uncover patterns consistent with the possibility of positive selection for m.3243A>G. Germline selection of m.3243A>G shows an arching profile by which selection is positive at intermediate mutant fractions and declines at high and low mutant fractions. We conclude that use of this biphasic approach will greatly improve the accuracy of modelling changes in mtDNA mutation frequencies in the germline and in somatic cells during aging.

genomics↗

bioRxiv2021

Metagenomes from the Loxahatchee wildlife refuge in the Florida Everglades

The Florida Everglades ecosystem represents a significant wetlands area and serves as a terrestrial carbon reservoir mediated in large part by microorganisms. Shotgun metagenome sequencing provides a snapshot of microbial diversity and the frequency of metabolic and functional gene content. Here, we present an analysis of 20 sediment samples collected from the Arthur R. Marshall Loxahatchee National Wildlife Refuge to characterize the taxonomic and functional potential of the microbial and viral communities, and reconstructed metagenome-assembled genomes. A total of 122 medium-quality and 6 high-quality MAGs are reported, three of which likely represent a novel species within the class Dehalococcoidia. The most abundant phyla of bacteria and archaea were Proteobacteria and Euryarchaeota, respectively. Caudovirales was the most abundant viral order. Significant differences in taxonomic composition and diversity were observed among collection sites. Additionally, water samples were analyzed for pH, total nitrogen, total organic carbon, elements (P, K, Mg, Fe, Mn, Pb, Ca, S), chloride, electric conductivity, orthophosphate, nitrate, and ammonia, while the sediment samples were analyzed for carbon, nitrogen, and pH. Differences in measured aquatic and sediment analytes revealed significant correlations with numerous phyla. Significant correlations were observed between estimated gene frequencies of both aquatic and sediment analytes, most notably between kup/kdpB and dsrA/cysC with potassium and sulfur, respectively, as well as phoD/phnX and cysC with pH. Together, these data provide an important view into the functional and metabolic potential encoded within the sediment microbial communities in the Florida Everglades.

microbiology↗

bioRxiv2021

The ETS Transcription Factor ERF controls the exit from the naive pluripotent state

The naive epiblast undergoes a transition to a pluripotent primed state during embryo implantation. Despite the relevance of the FGF pathway during this period, little is known about the downstream effectors regulating this signaling. Here, we examined the molecular mechanisms coordinating the naive to primed transition by using inducible ESC to genetically eliminate all RAS proteins. We show that differentiated RASKO ESC remain trapped in an intermediate state of pluripotency with naive-associated features. Elimination of the transcription factor ERF overcomes the developmental blockage of RAS-deficient cells by naive enhancer decommissioning. Mechanistically, ERF regulates NANOG expression and ensures naive pluripotency by strengthening naive transcription factor binding at ESC enhancers. Moreover, ERF negatively regulates the expression of the de novo methyltransferase DNMT3B, which participates in the extinction of the naive transcriptional program. Collectively, we demonstrated an essential role for ERF controlling the exit from naive pluripotency during the progression to primed pluripotency. TeaserERF is the MAPK-dependent switch controlling the transition between naive and primed pluripotency during embryonic development.

developmental biology↗

bioRxiv2020

CTCF is a Barrier for Totipotent-like Reprogramming

Totipotent cells have the ability of generating embryonic and extra-embryonic tissues1,2. Interestingly, a rare population of cells with totipotent-like potential was identified within ESC cultures3. These cells, known as 2 cell (2C)-like cells, arise from ESC and display similar features to those found in the totipotent 2 cell embryo2-4. However, the molecular determinants of 2C-like conversion have not been completely elucidated. Here, we show that CTCF is a barrier for 2C-like reprogramming. Indeed, forced conversion to a 2C-like state by DUX expression was associated with DNA damage at a subset of CTCF binding sites. Endogenous or DUX-induced 2C-like ESC showed decreased CTCF enrichment at known binding sites, suggesting that acquisition of a totipotent-like state is associated with a highly dynamic chromatin architecture. Accordingly, depletion of CTCF in ESC efficiently promoted spontaneous and asynchronous conversion to a totipotent-like state. This phenotypic reprogramming was reversible upon restoration of CTCF levels. Furthermore, we showed that transcriptional activation of the ZSCAN4 cluster was necessary for successful 2C-like reprogramming. In summary, we revealed the intimate relation between CTCF and totipotent-like reprogramming.

developmental biology↗

bioRxiv2020

Rapid in silico design of antibodies targeting SARS-CoV-2 using machine learning and supercomputing

Rapidly responding to novel pathogens, such as SARS-CoV-2, represents an extremely challenging and complex endeavor. Numerous promising therapeutic and vaccine research efforts to mitigate the catastrophic effects of COVID-19 pandemic are underway, yet an efficacious countermeasure is still not available. To support these global research efforts, we have used a novel computational pipeline combining machine learning, bioinformatics, and supercomputing to predict antibody structures capable of targeting the SARS-CoV-2 receptor binding domain (RBD). In 22 days, using just the SARS-CoV-2 sequence and previously published neutralizing antibody structures for SARS-CoV-1, we generated 20 initial antibody sequences predicted to target the SARS-CoV-2 RBD. As a first step in this process, we predicted (and publicly released) structures of the SARS-CoV-2 spike protein using homology-based structural modeling. The predicted structures proved to be accurate within the targeted RBD region when compared to experimentally derived structures published weeks later. Next we used our in silico design platform to iteratively propose mutations to SARS-CoV-1 neutralizing antibodies (known not to bind SARS-Cov-2) to enable and optimize binding within the RBD of SARS-CoV-2. Starting from a calculated baseline free energy of -48.1 kcal/mol ({+/-} 8.3), our 20 selected first round antibody structures are predicted to have improved interaction with the SARS-CoV-2 RBD with free energies as low as -82.0 kcal/mole. The baseline SARS-CoV-1 antibody in complex with the SARS-CoV-1 RBD has a calculated interaction energy of -52.2 kcal/mole and neutralizes the virus by preventing it from binding and entering the human ACE2 receptor. These results suggest that our predicted antibody mutants may bind the SARS-CoV-2 RBD and potentially neutralize the virus. Additionally, our selected antibody mutants score well according to multiple antibody developability metrics. These antibody designs are being expressed and experimentally tested for binding to COVID-19 viral proteins, which will provide invaluable feedback to further improve the machine learning-driven designs. This technical report is a high-level description of that effort; the Supplementary Materials includes the homology-based structural models we developed and 178,856 in silico free energy calculations for 89,263 mutant antibodies derived from known SARS-CoV-1 neutralizing antibodies.

bioinformatics↗

bioRxiv2020

EFA6B regulates a stop signal for collective invasion in breast cancer

Cancer is initiated by somatic mutations in oncogenes or tumor suppressor genes, however additional mutations provide selective advantages to the tumor cells to resist treatment and develop metastases, therefore identification of secondary mutations is of paramount importance. EFA6B (Exchange Factor for ARF6, B) expression is reduced in breast cancer. To study the pro-tumoral impact of the loss of EFA6B we have invalidated its gene in normal human mammary cells. We found that EFA6B knock-out triggers a transcriptional reprogramming of the cell-to-ECM interaction machinery and unleashes CDC42-dependent collective invasion in collagen. In addition, invasive and metastatic tumors isolated from patients have lower expression of EFA6B and display gene ontology signatures identical to those of EFA6B knock-out cells. Thus, we reveal a new EFA6B-regulated molecular mechanism that controls the invasive potential of mammary cells; this finding opens up new avenues for the treatment of invasive breast cancer.

cancer biology↗

bioRxiv2020

The physical form of microbial ligands bypasses the need for dendritic cell migration to stimulate adaptive immunity

A central paradigm of immunology is that the innate immune system first detects infectious agents in peripheral tissues, shortly after a pathogen has breached an epithelial barrier. This detection event is mediated by pattern recognition receptors in phagocytes, which then migrate to draining lymph nodes (dLNs), where information of a microbial encounter is conveyed to T and B lymphocytes to generate adaptive immunity. Through the study of fungal moieties, we present data that challenge this model. We found that soluble fungal polysaccharides are immunosilent in the periphery, but become potent immunogens in the dLN. These ligands completely bypass the need of phagocyte migration and, instead, directly activate an immune response that is most similar to those that typify viral infections. These data establish a class of microbial products that violate a central tenet of the immunological lexicon and illustrate that the physical form (not just the chemical structure) impacts innate and adaptive immunity.

immunology↗

bioRxiv2019

Aberrant cell segregation in craniofacial primordia and the emergence of facial dysmorphology in craniofrontonasal syndrome

Craniofrontonasal syndrome (CFNS) is a rare X-linked disorder characterized by craniofacial, skeletal, and neurological anomalies and caused by mutations in EFNB1. Heterozygous females are more severely affected by CFNS than hemizygous male patients, a phenomenon called cellular interference that is correlated with cell segregation resulting from EPHRIN-B1 mosaicism. Efnb1 heterozygous mutant mice also exhibit more severe phenotypes than Efnb1 hemizygous males as well as cell segregation, but how craniofacial dysmorphology arises from cell segregation is unknown and CFNS etiology therefore remains poorly understood. Here, we couple geometric morphometric techniques with temporal and spatial interrogation of embryonic cell segregation in mouse models to elucidate mechanisms underlying CFNS pathogenesis. By generating ephrin-B1 mosaicism at different developmental timepoints and in specific cell populations, we find that ephrin-B1 regulates cell segregation independently in early neural development and later in craniofacial development, correlating with the emergence of quantitative differences in face shape. Whereas specific craniofacial shape changes are qualitatively similar in Efnb1 heterozygous and hemizygous mutant embryos, heterozygous embryos are quantitatively more severely affected, indicating that Efnb1 mosaicism exacerbates loss of function phenotypes rather than having a neomorphic effect. Notably, tissue-specific disruption of Efnb1 throughout neural development does not appear to contribute to CFNS dysmorphology, but its disruption within neural crest cell-derived mesenchyme results in phenotypes very similar to widespread loss. Ephrin-B1 can bind and signal with EphB1, EphB2, and EphB3 receptor tyrosine kinases, but the signaling partner(s) relevant to CFNS are unknown. Geometric morphometric analysis of an allelic series of Ephb1; Ephb2; Ephb3 mutant embryos indicates that EphB2 and EphB3 are key receptors mediating Efnb1 hemizygous-like phenotypes, but the complete loss of EphB1-3 does not recapitulate CFNS-like Efnb1 heterozygous severity. Finally, by generating Efnb1+/-; Ephb1; Ephb2; Ephb3 quadruple knockout mice, we determine how modulating cumulative receptor activity influences cell segregation in craniofacial development and find that while EphB2 and EphB3 play an important role in craniofacial cell segregation, EphB1 is more important for cell segregation in the brain; surprisingly, complete loss of EphB1-EphB3 does not completely abrogate cell segregation. Together, these data advance our understanding of the morphogenetic etiology and signaling interactions underlying CFNS dysmorphology.\n\nAuthor SummaryCraniofacial anomalies are extremely common, accounting for one third of all birth defects, but even when the responsible genes are known, it often remains to be determined exactly how development has gone wrong. Craniofrontonasal syndrome (CFNS), which affects multiple aspects of craniofacial development, is a particularly mysterious disorder because it is X-linked, but affects females more severely than males, the opposite situation of most X-linked diseases. The responsible gene has been identified as EFNB1, which encodes the EPHRIN-B1 signaling molecule that regulates cellular position. Why EFNB1+/- heterozygous females exhibit severe stereotypical CFNS phenotypes is not well understood, but it is related to the fact that X chromosome inactivation generates mosaicism for EPHRIN-B1. Using mice harboring mutations in the Efnb1 gene in different embryonic tissues, and in receptor genes Ephb1-3, together with quantitative methods to measure craniofacial structures in developing embryos, we establish the tissue-specific contributions of ephrin-B1 mosaicism to craniofacial dysmorphology. We also examine when ephrin-B1 regulates cellular position during different stages of craniofacial development and which EphB receptors are involved. Our results reveal the specific cellular context and signaling interactions that are likely to underlie CFNS, and provide new understanding of how EPHRIN-B1 may regulate normal craniofacial development.

developmental biology↗

bioRxiv2019

Quasi-Mendelian Paternal Inheritance of mitochondrial DNA: A notorious artifact, or anticipated mtDNA behavior?

A recent report by Luo et al (2018) in PNAS (DOI:10.1073/pnas.1810946115) presented evidence of biparental inheritance of mitochondrial DNA. The pattern of inheritance, however, resembled that of a nuclear gene. The authors explained this peculiarity with Mendelian segregation of a faulty gatekeeper gene that permits survival of paternal mtDNA in the oocyte. Three other groups (Vissing, 2019; Lutz-Bonengel and Parson, 2019; Salas et al, 2019), however, posited the observation was an artifact of inheritance of mtDNA nuclear pseudogenes (NUMTs), present in the fathers nuclear genome. We present justification that both interpretations are incorrect, but that the original authors did, in fact, observe biparental inheritance of mtDNA. Our alternative model assumes that because of initially low paternal mtDNA copy number these copies are randomly partitioned into nascent cell lineages. The paternal mtDNA haplotype must have a selective advantage, so seeded cells will tend to proceed to fixation of the paternal haplotype in the course of development. We use modeling to emulate the dynamics of paternal genomes and predict their mode of inheritance and distribution in somatic tissue. The resulting offspring is a mosaic of cells that are purely maternal or purely paternal - including in the germline. This mosaicism explains the quasi-Mendelian segregation of the paternal mDNA. Our model is based on known aspects of mtDNA biology and explains all of the experimental observations outlined in Luo et. al., including maternal inheritance of the grand-paternal mtDNA.

genetics↗

bioRxiv2019

Mitochondrial mutational spectrum provides an universal marker of cellular and organismal longevity

Mutational spectrum of the mitochondrial genome (mtDNA) does not resemble signatures of any known mutagens and variation in mtDNA mutational spectra between different tissues and organisms is still incomprehensible. Since mitochondria is tightly involved in aerobic energy production, it is expected that mtDNA mutational spectra may be affected by the oxidative damage which is increasing with cellular and organismal aging. However, the well-documented mutational signature of the oxidative damage, G>T substitutions, is typical only for the nuclear genome while it is extremely rare and age-independent in mtDNA. Thus it is still unclear if there is a mitochondria - specific mutational signature of the oxidative damage. Here, reconstructing mtDNA mutational spectra for human cancers originated from 21 tissues with various cell turnover rate, human oocytes fertilized at different ages, and 424 mammalian species with variable generation length which is a proxy for oocyte age, we observed that the frequency of AH>GH substitutions (H - heavy chain notation) is positively correlated with cellular and organismal longevity. Moreover, this mutational bias from AH to GH affects nucleotide content at the fourfold degenerative synonymous positions leading to a deficit of AH and excess of GH, which is especially pronounced in long-lived mammals. Taking into account additionally, that AH>GH is sensitive to time being single stranded during mtDNA asynchronous replication and A>G is associated with oxidative damage of single-stranded DNA in recent bacterial experiments we propose that AH>GH is a mutational signature of oxidative damage in mtDNA.

genomics↗

bioRxiv2018

Prediction of response to anti-cancer drugs becomes robust via network integration of molecular data

In order to tackle heterogeneity of cancer samples and high data space dimensionality, we propose a method NEAmarker for finding sensitive and robust biomarkers at the pathway level. In this method, scores from network enrichment analysis transform the original space of altered genes into a lower-dimensional space of pathways, which is then correlated with phenotype variables. The analysis was first done on in vitro anti-cancer drug screen datasets and then on clinical data. In parallel, we tested a panel of state-of-the-art enrichment methods. In this comparison, our method proved superior in terms of 1) universal applicability to different data types with a possibility of cross-platform integration, 2) consistency of the discovered correlates between independent drug screens, and 3) ability to explain differential survival of treated patients. Our new in vitro screen validated performance of the discovered multivariate models. Finally, NEAmarker was the only method to discover predictors of both in vitro response and patient survival given administration of the same drug.

cancer biology↗