Reassessing the modularity of gene co-expression networks using the Stochastic Block Model.

Finding communities in gene co-expression networks is a common first step toward extracting biological insight from these complex datasets. Most community detection algorithms expect genes to be organized into assortative modules, that is, groups of genes that are more associated with each other than with genes in other groups. While it is reasonable to expect that these modules exist, using methods that assume they exist a priori is risky, as it guarantees that alternative organizations of gene interactions will be ignored. Here, we ask: can we find meaningful communities without imposing a modular organization on gene co-expression networks, and how modular are these communities? For this, we use a recently developed community detection method, the weighted degree corrected stochastic block model (SBM), that does not assume that assortative modules exist. Instead, the SBM attempts to efficiently use all information contained in the co-expression network to separate the genes into hierarchically organized blocks of genes. Using RNA-seq gene expression data measured in two tissues derived from an outbred population of, we show that (a) the SBM is able to find ten times as many groups as competing methods, that (b) several of those gene groups are not modular, and that (c) the functional enrichment for non-modular groups is as strong as for modular communities. These results show that the transcriptome is structured in more complex ways than traditionally thought and that we should revisit the long-standing assumption that modularity is the main driver of the structuring of gene co-expression networks.

Wolbachia impacts microbiome diversity and fitness-associated traits for Drosophila melanogaster in a seasonally fluctuating environment.

The microbiome contributes to many different host traits, but its role in host adaptation remains enigmatic. The fitness benefits of the microbiome often depend on ecological conditions, but theory suggests that fluctuations in both the microbiome and environment modulate these fitness benefits. Moreover, vertically transmitted bacteria might constrain the ability of both the microbiome and host to respond to changing environments. Drosophila melanogaster provides an excellent system to investigate the impacts of interactions between the microbiome and the environment. To address this question, we created field mesocosms of D. melanogaster undergoing seasonal environmental change with and without the vertically transmitted bacteria, Wolbachia pipientis. Sampling temporal patterns in the microbiome revealed that Wolbachia constrained microbial diversity. Furthermore, Wolbachia and a dominant member of the microbiome, Commensalibacter, were associated with differences in two higher-order fitness traits, starvation resistance and lifespan. Our work here suggests that the interplay between the abiotic context and microbe-microbe interactions may shape key host phenotypes that underlie adaptation to changing environments. We conclude by exploring the consequences of complex interactions between Wolbachia and the microbiome for our understanding of eco-evolutionary processes that shape host-microbiome interactions.

Vibrational Circular Dichroism of a Chiral Triplet Nitrene Investigated Under Matrix-Isolation Conditions in Parahydrogen.

Vibrational circular dichroism (VCD) spectra of chiral high-spin organic radicals are expected to show a strong intensity enhancement and are thought to be difficult to predict using state-of-the-art theoretical methods. Herein we show that the chiral triplet nitrene obtained from photochemical cleavage of N2 from enantiopure 2-azido-9H-fluorenol does not feature extraordinarily strong intensities and that the experimental spectra match nicely with calculated ones. Thereby, this study demonstrates the general feasibility of studies on chiral high-spin organics by matrix-isolation VCD.

Drug- and Toxin-Induced Opsoclonus - a Systematized Review, including a Case Report on Amantadine-Induced Opsoclonus in Multiple System Atrophy.

Background: Opsoclonus is a rare disorder characterized by conjugate multidirectional, horizontal, vertical, and torsional saccadic oscillations, without intersaccadic interval, resulting from dysfunction within complex neuronal pathways in the brainstem and cerebellum. While most cases of opsoclonus are associated with autoimmune or paraneoplastic disorders, infectious agents, trauma, or remain idiopathic, opsoclonus can also be caused by medications affecting neurotransmission. This review was prompted by a case of opsoclonus occurring in a patient with Multiple System Atrophy, where amantadine, an NMDA-receptor antagonist, appeared to induce opsoclonus. Methods: Case report of a single patient and systematized review of toxic/drug-induced opsoclonus, selecting articles based on predefined criteria and assessing the quality of included studies. Results: The review included 30 articles encompassing 158 cases of toxic/drug-induced opsoclonus. 74% of cases were attributed to bark scorpion poisoning, followed by 9% of cases associated with chlordecone intoxication. The remaining cases were due to various toxics/drugs, highlighting the involvement of various neurotransmitters, including acetylcholine, glutamate, GABA, dopamine, glycine, and sodium channels, in the development of opsoclonus. Conclusion: Toxic/drug-induced opsoclonus is very rare. The diversity of toxics/drugs impacting different neurotransmitter systems makes it challenging to define a unifying mechanism, given the intricate neuronal pathways underlying eye movement physiology and opsoclonus pathophysiology.

Determinants of microbiome composition: Insights from free-ranging hybrid zebras (Equus quagga × grevyi).

The composition of mammalian gut microbiomes is highly conserved within species, yet the mechanisms by which microbiome composition is transmitted and maintained within lineages of wild animals remain unclear. Mutually compatible hypotheses exist, including that microbiome fidelity results from inherited dietary habits, shared environmental exposure, morphophysiological filtering and/or maternal effects. Interspecific hybrids are a promising system in which to interrogate the determinants of microbiome composition because hybrids can decouple traits and processes that are otherwise co-inherited in their parent species. We used a population of free-living hybrid zebras (Equus quagga × grevyi) in Kenya to evaluate the roles of these four mechanisms in regulating microbiome composition. We analysed faecal DNA for both the trnL-P6 and the 16S rRNA V4 region to characterize the diets and microbiomes of the hybrid zebra and of their parent species, plains zebra (E. quagga) and Grevy's zebra (E. grevyi). We found that both diet and microbiome composition clustered by species, and that hybrid diets and microbiomes were largely nested within those of the maternal species, plains zebra. Hybrid microbiomes were less variable than those of either parent species where they co-occurred. Diet and microbiome composition were strongly correlated, although the strength of this correlation varied between species. These patterns are most consistent with the maternal-effects hypothesis, somewhat consistent with the diet hypothesis, and largely inconsistent with the environmental-sourcing and morphophysiological-filtering hypotheses. Maternal transmittance likely operates in conjunction with inherited feeding habits to conserve microbiome composition within species.

YY1 mutations disrupt corticogenesis through a cell-type specific rewiring of cell-autonomous and non-cell-autonomous transcriptional programs.

Germline mutations of YY1 cause Gabriele-de Vries syndrome (GADEVS), a neurodevelopmental disorder featuring intellectual disability and a wide range of systemic manifestations. To dissect the cellular and molecular mechanisms underlying GADEVS, we combined large-scale imaging, single-cell multiomics and gene regulatory network reconstruction in 2D and 3D patient-derived physiopathologically relevant cell lineages. YY1 haploinsufficiency causes a pervasive alteration of cell type specific transcriptional networks, disrupting corticogenesis at the level of neural progenitors and terminally differentiated neurons, including cytoarchitectural defects reminiscent of GADEVS clinical features. Transcriptional alterations in neurons propagated to neighboring astrocytes through a major non-cell autonomous pro-inflammatory effect that grounds the rationale for modulatory interventions. Together, neurodevelopmental trajectories, synaptic formation and neuronal-astrocyte cross talk emerged as salient domains of YY1 dosage-dependent vulnerability. Mechanistically, cell-type resolved reconstruction of gene regulatory networks uncovered the regulatory interplay between YY1, NEUROG2 and ETV5 and its aberrant rewiring in GADEVS. Our findings underscore the reach of advanced in vitro models in capturing developmental antecedents of clinical features and exposing their underlying mechanisms to guide the search for targeted interventions.

Reassessing the modularity of gene co-expression networks using the Stochastic Block Model.

Finding communities in gene co-expression networks is a common first step toward extracting biological insight from these complex datasets. Most community detection algorithms expect genes to be organized into assortative modules, that is, groups of genes that are more associated with each other than with genes in other groups. While it is reasonable to expect that these modules exist, using methods that assume they exist a priori is risky, as it guarantees that alternative organizations of gene interactions will be ignored. Here, we ask: can we find meaningful communities without imposing a modular organization on gene co-expression networks, and how modular are these communities? For this, we use a recently developed community detection method, the weighted degree corrected stochastic block model (SBM), that does not assume that assortative modules exist. Instead, the SBM attempts to efficiently use all information contained in the co-expression network to separate the genes into hierarchically organized blocks of genes. Using RNA-seq gene expression data measured in two tissues derived from an outbred population of Drosophila melanogaster , we show that (a) the SBM is able to find ten times as many groups as competing methods, that (b) several of those gene groups are not modular, and that (c) the functional enrichment for non-modular groups is as strong as for modular communities. These results show that the transcriptome is structured in more complex ways than traditionally thought and that we should revisit the long-standing assumption that modularity is the main driver of the structuring of gene co-expression networks.

Deep Brain Stimulation Improves Parkinson's Disease-Associated Pain by Decreasing Spinal Nociception.

Dopamine exerts antinociceptive effects on pain in PD at cortical and spinal levels, whereas only cortical effects have been described for DBS, so far. By assessing the nociceptive flexion reflex (NFR) threshold at medication on, and DBS ON and OFF in two patients, we showed that DBS additionally decreases spinal nociception.

Exercise and gait/movement analyses in treatment and diagnosis of Parkinson's Disease.

Cardinal motor symptoms in Parkinson's disease (PD) include bradykinesia, rest tremor and/or rigidity. This symptomatology can additionally encompass abnormal gait, balance and postural patterns at advanced stages of the disease. Besides pharmacological and surgical therapies, physical exercise represents an important strategy for the management of these advanced impairments. Traditionally, diagnosis and classification of such abnormalities have relied on partially subjective evaluations performed by neurologists during short and temporally scattered hospital appointments. Emerging sports medical methods, including wearable sensor-based movement assessment and computational-statistical analysis, are paving the way for more objective and systematic diagnoses in everyday life conditions. These approaches hold promise to facilitate customizing clinical trials to specific PD groups, as well as personalizing neuromodulation therapies and exercise prescriptions for each individual, remotely and regularly, according to disease progression or specific motor symptoms. We aim to summarize exercise benefits for PD with a specific emphasis on gait and balance deficits, and to provide an overview of recent advances in movement analysis approaches, notably from the sports science community, with value for diagnosis and prognosis. Although such techniques are becoming increasingly available, their standardization and optimization for clinical purposes is critically missing, especially in their translation to complex neurodegenerative disorders such as PD. We highlight the importance of integrating state-of-the-art gait and movement analysis approaches, in combination with other motor, electrophysiological or neural biomarkers, to improve the understanding of the diversity of PD phenotypes, their response to therapies and the dynamics of their disease progression.

No fitness cost entailed by type VI secretion system synthesis, assembly, contraction, or disassembly in enteroaggregative Escherichia coli.

IMPORTANCE: Bacteria use weapons to deliver effectors into target cells. One of these weapons, the type VI secretion system (T6SS), assembles a contractile tail acting as a spring to propel a toxin-loaded needle. Due to its size and mechanism of action, the T6SS was intuitively thought to be energetically costly. Here, using a combination of mutants and growth measurements in liquid medium, on plates, and in competition experiments, we show that the T6SS does not entail a growth cost to enteroaggregative Escherichia coli.

A spinal cord neuroprosthesis for locomotor deficits due to Parkinson's disease.

People with late-stage Parkinson's disease (PD) often suffer from debilitating locomotor deficits that are resistant to currently available therapies. To alleviate these deficits, we developed a neuroprosthesis operating in closed loop that targets the dorsal root entry zones innervating lumbosacral segments to reproduce the natural spatiotemporal activation of the lumbosacral spinal cord during walking. We first developed this neuroprosthesis in a non-human primate model that replicates locomotor deficits due to PD. This neuroprosthesis not only alleviated locomotor deficits but also restored skilled walking in this model. We then implanted the neuroprosthesis in a 62-year-old male with a 30-year history of PD who presented with severe gait impairments and frequent falls that were medically refractory to currently available therapies. We found that the neuroprosthesis interacted synergistically with deep brain stimulation of the subthalamic nucleus and dopaminergic replacement therapies to alleviate asymmetry and promote longer steps, improve balance and reduce freezing of gait. This neuroprosthesis opens new perspectives to reduce the severity of locomotor deficits in people with PD.

Relative abundance data can misrepresent heritability of the microbiome.

BACKGROUND: Host genetics can shape microbiome composition, but to what extent it does, remains unclear. Like any other complex trait, this important question can be addressed by estimating the heritability (h2) of the microbiome-the proportion of variance in the abundance in each taxon that is attributable to host genetic variation. However, unlike most complex traits, microbiome heritability is typically based on relative abundance data, where taxon-specific abundances are expressed as the proportion of the total microbial abundance in a sample. RESULTS: We derived an analytical approximation for the heritability that one obtains when using such relative, and not absolute, abundances, based on an underlying quantitative genetic model for absolute abundances. Based on this, we uncovered three problems that can arise when using relative abundances to estimate microbiome heritability: (1) the interdependency between taxa can lead to imprecise heritability estimates. This problem is most apparent for dominant taxa. (2) Large sample size leads to high false discovery rates. With enough statistical power, the result is a strong overestimation of the number of heritable taxa in a community. (3) Microbial co-abundances lead to biased heritability estimates. CONCLUSIONS: We discuss several potential solutions for advancing the field, focusing on technical and statistical developments, and conclude that caution must be taken when interpreting heritability estimates and comparing values across studies. Video Abstract.

Applying an evolutionary mismatch framework to understand disease susceptibility.

Noncommunicable diseases (NCDs) are on the rise worldwide. Obesity, cardiovascular disease, and type 2 diabetes are among a long list of "lifestyle" diseases that were rare throughout human history but are now common. The evolutionary mismatch hypothesis posits that humans evolved in environments that radically differ from those we currently experience; consequently, traits that were once advantageous may now be "mismatched" and disease causing. At the genetic level, this hypothesis predicts that loci with a history of selection will exhibit "genotype by environment" (GxE) interactions, with different health effects in "ancestral" versus "modern" environments. To identify such loci, we advocate for combining genomic tools in partnership with subsistence-level groups experiencing rapid lifestyle change. In these populations, comparisons of individuals falling on opposite extremes of the "matched" to "mismatched" spectrum are uniquely possible. More broadly, the work we propose will inform our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and cultures.

GC-FTICR mass spectrometry with dopant assisted atmospheric pressure photoionization: application to the characterization of plastic pyrolysis oil.

Pyrolysis is a promising way to convert plastic waste into valuable resources. However, for downstream upgrading processes, many undesirable species, such as conjugated diolefins or heteroatom-containing compounds, can be generated during this pyrolysis. In-depth chemical characterization is therefore required to improve conversion and valorization. Because of the high molecular diversity found in these samples, advanced analytical instrumentation is needed to provide accurate and complete characterization. Generally, direct infusion Fourier transform mass spectrometry is used to gather information at the molecular level, but it has the disadvantage of limited structural insights. To overcome this drawback, gas chromatography has been coupled to Fourier transform ion cyclotron resonance mass spectrometry. By taking advantage of soft atmospheric pressure photoionization, which preserves molecular information, and the use of different dopants (pyrrole, toluene, and benzene), selective ionization of different chemical families was achieved. Differences in the ionization energy of the dopants will only allow the ionization of the molecules of the pyrolysis oil which have lower ionization energy, or which are accessible via specific chemical ionization pathways. With a selective focus on hydrocarbon species and especially hydrocarbon species having a double bond equivalent (DBE) value of 2, pyrrole is prone to better ionize low-mass molecules with lower retention times compared to the dopant benzene, which allowed better ionization of high-mass molecules with higher retention times. The toluene dopant presented the advantage of ionizing both low and high mass molecules.

Capturing continuous, long timescale behavioral changes in Drosophila melanogaster postural data.

Animal behavior spans many timescales, from short, seconds-scale actions to circadian rhythms over many hours to life-long changes during aging. Most quantitative behavior studies have focused on short-timescale behaviors such as locomotion and grooming. Analysis of these data suggests there exists a hierarchy of timescales; however, the limited duration of these experiments prevents the investigation of the full temporal structure. To access longer timescales of behavior, we continuously recorded individual Drosophila melanogaster at 100 frames per second for up to 7 days at a time in featureless arenas on sucrose-agarose media. We use the deep learning framework SLEAP to produce a full-body postural data set for 47 individuals resulting in nearly 2 billion pose instances. We identify stereotyped behaviors such as grooming, proboscis extension, and locomotion and use the resulting ethograms to explore how the flies' behavior varies across time of day and days in the experiment. We find distinct circadian patterns in all of our stereotyped behavior and also see changes in behavior over the course of the experiment as the flies weaken and die.

Characterizing the landscape of gene expression variance in humans.

Gene expression variance has been linked to organismal function and fitness but remains a commonly neglected aspect of molecular research. As a result, we lack a comprehensive understanding of the patterns of transcriptional variance across genes, and how this variance is linked to context-specific gene regulation and gene function. Here, we use 57 large publicly available RNA-seq data sets to investigate the landscape of gene expression variance. These studies cover a wide range of tissues and allowed us to assess if there are consistently more or less variable genes across tissues and data sets and what mechanisms drive these patterns. We show that gene expression variance is broadly similar across tissues and studies, indicating that the pattern of transcriptional variance is consistent. We use this similarity to create both global and within-tissue rankings of variation, which we use to show that function, sequence variation, and gene regulatory signatures contribute to gene expression variance. Low-variance genes are associated with fundamental cell processes and have lower levels of genetic polymorphisms, have higher gene-gene connectivity, and tend to be associated with chromatin states associated with transcription. In contrast, high-variance genes are enriched for genes involved in immune response, environmentally responsive genes, immediate early genes, and are associated with higher levels of polymorphisms. These results show that the pattern of transcriptional variance is not noise. Instead, it is a consistent gene trait that seems to be functionally constrained in human populations. Furthermore, this commonly neglected aspect of molecular phenotypic variation harbors important information to understand complex traits and disease.

Contribution of LDI and MALDI for the Characterization of a Lignocellulosic-Based Pyrolysis Bio-Oil.

In recent years, various alternatives to fossil fuels have been developed. One of them involves the production of bio-oils from lignocellulosic-based biomass through pyrolysis. However, bio-oils present numerous heteroatoms and, in particular, oxygen atoms that need to be removed by an upgrading process. To optimize these processes, it is necessary to have good knowledge of the composition of the bio-oils at the molecular level. This work aims to establish the usefulness of laser desorption ionization (LDI) and matrix-assisted laser desorption/ionization (MALDI) techniques on lignocellulosic biomass-based bio-oils. Using a Fourier transform ion cyclotron mass spectrometer (FTICR MS), we showed that MALDI gives more information than LDI. The selectivity of a series of MALDI matrices was investigated, showing that some matrices are selective toward compound families and others ionize a wider range of compounds. In this study, nine proton-transfer matrices and three electron-transfer matrices were used and compared to results obtained in LDI. Dithranol, acetosyringone, and graphene oxide were the three promising matrices selected from all matrices, giving an overall characterization of oxygenated classes in a bio-oil. They allowed the ionization of many more species covering a wide range of polarity, aromaticity, and mass with a homogeneous relative intensity for all molecular classes such as lignin-derivative species, sugars, and lipid-derivative species.

Isomer-Specific Heavy-Atom Tunneling in the Ring Expansion of Fluorenylazirines.

The photolysis of 2-azidofluorene in solid argon at 3 K results in the formation of 2-fluorenylnitrene. The nitrene undergoes subsequent rearrangements to two isomeric didehydroazepines (ketenimines) which differ in the position of the N atom in the seven-membered ring. The rearrangement of the nitrene to the didehydroazepines proceeds in a two-step process. The first step is a photochemical rearrangement to form the corresponding isomeric benzazirines A and B. The second step is the opening of the three-membered rings of A and B to form the isomeric didehydroazepines. While benzazirine A could easily be detected, isomer B was not observed, despite the corresponding didehydroazepine being formed in the matrix. Further experiments revealed that A rearranges to the didehydroazepine via heavy-atom tunneling. Semiquantitative estimations based on DFT calculations confirm that A should undergo a tunneling rearrangement with tunneling rates on the order of the experimentally observed rates. In contrast, estimations for B suggest that for this isomer the tunneling rates should be much larger, resulting in lifetimes too short to be observable under the conditions of matrix isolation. These experiments demonstrate the influence of position isomerism on quantum tunneling rates.