Miracle-dz/UniFAR-FTUs huggingface dataset:
Fifty Generations of Amitosis: Tracing Asymmetric Allele Segregation in Polyploid Cells with Single-Cell DNA Sequencing

Amitosis is a widespread form of unbalanced nuclear division whose biomedical and evolutionary significance remain unclear. Traditionally, insights into the genetics of amitosis are acquired by assessing the rate of phenotypic assortment. The phenotypic diversification of heterozygous clones during successive cell divisions reveals the random segregation of alleles to daughter nuclei. Though powerful, this experimental approach relies on the availability of phenotypic markers. Here, we present an approach that overcomes the requirement for phenotypic assortment. Leveraging Paramecium tetraurelia, a unicellular eukaryote with nuclear dimorphism and a highly polyploid somatic nucleus, we use single-cell whole-genome sequencing to track the assortment of developmentally acquired somatic DNA variants. Accounting for genome representation biases, we measure the effect of amitosis on allele segregation across the first ∼50 amitotic divisions post self-fertilization and compare our empirical findings with theoretical predictions estimated via mathematical modeling. In line with our simulations, we show that amitosis in P. tetraurelia produces measurable but modest levels of somatic assortment. In forgoing the requirement for phenotypic assortment and employing developmental, environmentally induced somatic variation as molecular markers, our work provides a new powerful approach to investigate the consequences of amitosis in polyploid cells.
16S rRNA Amplicon Sequencing of Bagworm Metisa plana Walker (Lepidoptera: Psychidae)

The bagworm Metisa plana is one of the major pests in the oil palm plantation in Malaysia, with infestation that results in huge economical loss. Currently, the exact cause of the infestation is still undetermined. Studying the bacterial community of M. plana could provide insight on the problem as the bacteria associated with insects often provide numerous benefits to the insect itself. Using 16S rRNA amplicon sequencing, the study was conducted to compare the composition of the bacterial communities of two larval stages (early instar stage and late instar stage) from outbreak area, as well as comparing the late instar stage larvae from non-outbreak and outbreak areas. Generally, the bacterial community was dominated by Proteobacteria and Actinobacteria phyla while the Enterobacteriaceae was found to be the dominant family. When comparing between the early and late instar stage, Proteobacteria phylum was found to be more abundant in the late instar stage (82.36%) than in the early instar stage (82.28%). At the family level, the Enterobacteriaceae was slightly more abundant in late instar stage (75.46%) than in early instar stage (75.29%). The instar stage was observed to have no significant impact on the bacterial variability and showed similar bacterial community structure. When comparing between the non-outbreak area and outbreak, Proteobacteria was significantly more abundant in the outbreak area (82.02%) than in the non-outbreak area (20.57%). However, Actinobacteria was significantly more abundant in the non-outbreak area (76.29%) than in the outbreak area (14.16%). At the family level, Enterobacteriaceae was more abundant in outbreak area (75.41%) than in non-outbreak area (11.67%). Microbacteriaceae was observed to be more abundant in the non-outbreak area (70.87%) than in the outbreak area (12.47%). Although the result showed no significant difference in bacterial variability between different areas, it the bacterial community structure was significantly different.
Transcriptional activity and epigenetic regulation of transposable elements in the symbiotic fungus Rhizophagus irregularis

Arbuscular mycorrhizal (AM) fungi form mutualistic relationships with most land plant species. AM fungi have long been considered as ancient asexuals. Long-term clonal evolution would be remarkable for a eukaryotic lineage and suggests the importance of alternative mechanisms to promote genetic variability facilitating adaptation. Here, we assessed the potential of transposable elements (TEs) for generating genomic diversity. The dynamic expression of TEs during Rhizophagus irregularis spore development suggests ongoing TE activity. We find Mutator-like elements located near genes belonging to highly expanded gene families. Characterising the epigenomic status of R. irregularis provides evidence of DNA methylation and small RNA production occurring at TE loci. Our results support a potential role for TEs in shaping the genome, and roles for DNA methylation and small RNA-mediated silencing in regulating TEs. A well-controlled balance between TE activity and repression may therefore contribute to genome evolution in AM fungi.
Clinically Relevant Mutations of Mycobacterial GatCAB Inform Regulation of Translational Fidelity

Most bacteria use a two-step indirect pathway to aminoacylate tRNAGln and tRNAAsn, despite the fact that the indirect pathway consumes more energy and is error prone. We have previously shown that the higher protein synthesis errors from this indirect pathway in mycobacteria allow adaptation to hostile environments such as antibiotic treatment through generation of novel alternate proteins not coded by the genome. ABSTRACT Most bacteria employ a two-step indirect tRNA aminoacylation pathway for the synthesis of aminoacylated tRNAGln and tRNAAsn. The heterotrimeric enzyme GatCAB performs a critical amidotransferase reaction in the second step of this pathway. We have previously demonstrated in mycobacteria that this two-step pathway is error prone and translational errors contribute to adaptive phenotypes such as antibiotic tolerance. Furthermore, we identified clinical isolates of the globally important pathogen Mycobacterium tuberculosis with partial loss-of-function mutations in gatA, and demonstrated that these mutations result in high, specific rates of translational error and increased rifampin tolerance. However, the mechanisms by which these clinically derived mutations in gatA impact GatCAB function were unknown. Here, we describe biochemical and biophysical characterization of M. tuberculosis GatCAB, containing either wild-type gatA or one of two gatA mutants from clinical strains. We show that these mutations have minimal impact on enzymatic activity of GatCAB; however, they result in destabilization of the GatCAB complex as well as that of the ternary asparaginyl-transamidosome. Stabilizing complex formation with the solute trehalose increases specific translational fidelity of not only the mutant strains but also of wild-type mycobacteria. Therefore, our data suggest that alteration of GatCAB stability may be a mechanism for modulation of translational fidelity. IMPORTANCE Most bacteria use a two-step indirect pathway to aminoacylate tRNAGln and tRNAAsn, despite the fact that the indirect pathway consumes more energy and is error prone. We have previously shown that the higher protein synthesis errors from this indirect pathway in mycobacteria allow adaptation to hostile environments such as antibiotic treatment through generation of novel alternate proteins not coded by the genome. However, the precise mechanisms of how translational fidelity is tuned were not known. Here, we biochemically and biophysically characterize the critical enzyme of the Mycobacterium tuberculosis indirect pathway, GatCAB, as well as two mutant enzymes previously identified from clinical isolates that were associated with increased mistranslation. We show that the mutants dysregulate the pathway via destabilizing the enzyme complex. Importantly, increasing stability improves translational fidelity in both wild-type and mutant bacteria, demonstrating a mechanism by which mycobacteria may tune mistranslation rates.
Quantifying control circuit regulation in the human brain

As a field, control systems engineering has developed quantitative methods to characterize the regulation of systems or processes, whose functioning is ubiquitous within synthetic systems. In this context, a control circuit is objectively “well regulated” when discrepancy between desired and achieved output trajectories is minimized, and “robust” to the degree that it is able to regulate well in response to a wide range of stimuli. Most psychiatric disorders are assumed to reflect dysregulation of brain circuits. Yet, probing circuit regulation requires fundamentally different analytic strategies than the correlations relied upon for analyses of connectivity and their resultant networks. Here, we demonstrate how well-established methods for system identification in control systems engineering may be applied to functional magnetic resonance imaging (fMRI) data to extract generative computational models of human brain circuits. These provide two quantitative measures of direct relevance for psychiatric disorders: a circuit’s sensitivity to external perturbation and its dysregulation.
The 3D atlas builder: a dynamic and expandable 3D tool for monitoring the changes in the neuronal differentiation domain during hindbrain morphogenesis

Reconstruction of prototypic three-dimensional (3D) atlases at the scale of whole tissues or organs requires specific methods to be developed. We have established a protocol and provide experimental proof for building a digital 3D atlas (here, for zebrafish hindbrain) that integrates spatial and temporal data for neuronal differentiation and brain morphogenesis, through a combination of in vivo imaging techniques paired with image analyses and segmentation tools. First, we generated a reference 3D hindbrain from several imaged specimens and segmented them using a trainable tool; these were aligned using rigid registration, revealing distribution of neuronal differentiation patterns along the axes. Second, we quantified the dynamic growth of the neuronal differentiation domain vs. the progenitor domain in the whole hindbrain. Third, we used in vivo Kaede-photoconversion experiments to generate a temporal heatmap of the neuronal growth in the whole hindbrain, revealing the spatiotemporal dynamics of neuronal differentiation upon morphogenesis. Last, as proof-of-concept, we assessed the birthdate order of GABAergic neurons using our temporal registration map. As this protocol uses open-access tools and algorithms, it can be shared for standardized, accessible, tissue-wide cell population atlas construction.Brain morphogenesis studies can use our atlas-builder tool, which precisely maps cell populations in the embryonic brain over time and can be easily shared.
Interactions and information: exploring task allocation in ant colonies using network analysis

In animal societies, individuals may take on different roles to fulfil their own needs and the needs of their groups. Ant colonies display high levels of organisational complexity, with ants fulfilling different roles at different timescales (what is known as task allocation). Factors affecting task allocation can be at the individual level (e.g., physiology), or at the group level (e.g., the network of interactions). We focus on group level processes by exploring the relationship between interaction networks, task allocation and task switching using a previously published dataset (Mersch et al., 2013) tracking the behaviour of six Camponotus fellah colonies over 41 days. In our new analyses, our goal was to better explain the noisy process of task switching beyond simple age polyethism. First, we investigated the architecture of interaction networks using node (individual) level network measures and their relation to the individual’s task – foraging, cleaning or nursing – and whether or not the ant switched tasks. We then explored how noisy information propagation was among ants, as a function of the colony composition (how many ants carried out which tasks), through the information-theoretic metric of Effective Information. Our results show that interaction history was tied to task allocation: ants who switched to a task are more likely to have interacted with other ants carrying out that task. The degree to which interactions related to task allocation, as well as the noise in those interactions, depended on which groups of ants were interacting. Overall, we showed that colony cohesion was stable even as ant-level network measures varied more for ants when they switched functional groups; thus, ant colonies maintained a high level of information flow as determined by network analysis, and ant functional groups played different roles in maintaining colony cohesion through varied information flows. Highlights We analysed the interaction networks of six Camponotus fellah colonies We tested how centrality and information flow were tied to task switching Node-level network metrics and the information theoretic measure of Effective Information explained differences among functional groups Interactions were correlated with task switching, but the strength of the correlation differed across functional groups
ID-Seg: An Accurate and Reliable Infant Deep learning Segmentation Framework for Limbic Structures

Early postnatal period brain magnetic resonance imaging (MRI) is becoming an important approach to measure the impact of prenatal exposures on neurodevelopment and to investigate early biomarkers for risk. Among brain structures, Limbic structures are particular of interest in psychiatric disorder-related research. However, despite the promise of infant neuroimaging and the success of initial infant MRI studies, assessing limbic regions’ structure and function remains a significant challenge due to low inter-regional intensity contrast and high curvature (e.g., hippocampus). In addition, the agreement between existing automatic techniques and manual segmentation remains either untested or insufficient, particularly for the amygdala and hippocampus. In this work, we developed an accurate (based on three segmentation evaluation metrics), reliable and efficient infant deep learning segmentation framework (ID-Seg) to address the aforementioned challenges. Specifically, we leveraged a large dataset of 473 infant MRI scans to train ID-Seg and rigorously evaluated ID-Seg’s performance on internal and external datasets with manual segmentations. Compared with a state-of-the-art segmentation pipeline, we demonstrated that ID-Seg significantly improved the segmentation accuracy of limbic structures (hippocampus and amygdala) in newborn infants. Moreover, in a medium-size dataset, we found that ID-Seg-derived morphometric measures yield strong brain-behavior associations. As such, our ID-Seg may improve our capacity and efficiency to measure MRI-based brain features relevant to neuropsychological development and ultimately advance the success of quantitative analyses on large-scale datasets.
Correlative Organelle Microscopy: Fluorescence Guided Volume Electron Microscopy of Intracellular Processes

Intracellular processes depend on a strict spatial and temporal organization of proteins and organelles. Directly linking molecular to nanoscale ultrastructural information is therefore crucial to understand cellular physiology. Volume or 3-dimensional (3D) correlative light and electron microscopy (volume-CLEM) holds unique potential to explore cellular physiology at high-resolution ultrastructural detail across cell volumes. Application of volume-CLEM is however hampered by limitations in throughput and 3D correlation efficiency. Addressing these limitations, we here describe a novel pipeline for volume-CLEM that provides high-precision (<100nm) registration between 3D fluorescence microscopy (FM) and 3D electron microscopy (EM) data sets with significantly increased throughput. Using multi-modal fiducial nanoparticles that remain fluorescent in epoxy resins and a 3D confocal fluorescence microscope integrated in a Focused Ion Beam Scanning Electron Microscope (FIB.SEM), our approach uses FM to target extremely small volumes of even single organelles for imaging in volume-EM, and obviates the need for post correlation of big 3D datasets. We extend our targeted volume-CLEM approach to include live-cell imaging, adding information on the motility of intracellular membranes selected for volume-CLEM. We demonstrate the power of our approach by targeted imaging of rare and transient contact sites between endoplasmic reticulum (ER) and lysosomes within hours rather than days. Our data suggest that extensive ER-lysosome and mitochondria-lysosome interactions restrict lysosome motility, highlighting the unique capabilities of our integrated CLEM pipeline for linking molecular dynamic data to high-resolution ultrastructural detail in 3D. Significance We have developed a correlative imaging pipeline to (i) correlate 3D-FM to volume-EM data with high precision, directly bridging the FM and EM resolutions (ii) achieve high-throughput volume-CLEM by targeted EM imaging of a single organelle sized region-of-interest, pre-identified by FM (iii) link live-cell fluorescence imaging of cultured mammalian cells to high-throughput volume-CLEM (iv) quantitatively study structure-function relations at subcellular scale (v) link rare (e.g. membrane contact sites) and transient (e.g. organelle interactions) cellular events to 3D ultrastructure. The targeted volume-CLEM pipeline provides a unique prospect for multi-modal correlative intracellular analysis combining dynamic interaction (live-cell imaging), functional state (live-cell imaging), molecular localization (FM), and 3D-ultrastructure (FIB.SEM) at nanometer scale.
A stochastic pooling motif mediates information transfer from receptor assemblies into NF-κB

A myriad of inflammatory cytokines regulate signaling pathways to maintain cellular homeostasis. The IKK complex is an integration hub for cytokines that govern NF-κB signaling. In response to inflammation, IKK is activated through recruitment to receptor-associated protein assemblies. How and what information IKK complexes transmit about the milieu are open questions. Here we track dynamics of IKK complexes and nuclear NF-κB to identify upstream signaling features that determine same-cell responses. Experiments and modeling of single complexes reveals their size, number, and timing relays cytokine-specific control over shared signaling mechanisms with feedback regulation that is independent of transcription. Our results provide evidence for variable-gain stochastic pooling, a noise-reducing motif that enables cytokine-specific regulation and parsimonious information transfer. We propose that emergent properties of stochastic pooling are general principles of receptor signaling that have evolved for constructive information transmission in noisy molecular environments.
Taming strong selection with large sample sizes

The fate of mutations and the genetic load of populations depend on the relative importance of genetic drift and natural selection. In addition, the accuracy of numerical models of evolution depends on the strength of both selection and drift: strong selection breaks the assumptions of the nearly neutral model, and drift coupled with large sample sizes breaks Kingman’s coalescent model. Thus, the regime with strong selection and large sample sizes, relevant to the study of pathogenic variation, appears particularly daunting. Surprisingly, we find that the interplay of drift and selection in that regime can be used to define asymptotically closed recursions for the distribution of allele frequencies that are accurate well beyond the strong selection limit. Selection becomes more analytically tractable when the sample size n is larger than twice the population-scaled selection coefficient: n ≥ 2Ns (4Ns in diploids). That is, when the expected number of coalescent events in the sample is larger than the number of selective events. We construct the relevant transition matrices, show how they can be used to accurately compute distributions of allele frequencies, and show that the distribution of deleterious allele frequencies is sensitive to details of the evolutionary model.
A cryo-ET survey of intracellular compartments within mammalian axons

The neuronal axon contains many intracellular compartments which travel between the cell body and axon tip. The nature of these cargos and the complex axonal environment through which they traverse is unclear. Here, we describe the internal components of mammalian sensory axons using cryo-electron tomography. We show that axonal endoplasmic reticulum has thin, beaded appearance and is tethered to microtubules at multiple sites. The tethers are elongated, ∼ 7 nm long proteins which cluster in small groups. We survey the different membrane-bound cargos in axons, quantify their abundance and describe novel internal features including granules and broken membranes. We observe connecting density between membranes and microtubules which may correspond to motor proteins. In addition to membrane-bound organelles, we detect numerous proteinaceous compartments, including vaults and previously undescribed virus-like capsid particles. The abundance of these compartments suggests they undergo trafficking in axons. Our observations outline the physical characteristics of axonal cargo and provide a platform for identification of their constituents.
A systematic structural comparison of all solved small proteins (4-6 kDa) reveals the weight of disulfide bonds in proteins’ foldability

Defensins are small proteins, usually ranging from 4 to 6 kDa, amphipathic, disulfide-rich, and with a small or even absent hydrophobic core. Since a hydrophobic core is generally found in globular proteins that fold in an aqueous solvent, the peculiar fold of defensins can challenge tertiary protein structure predictors. We performed a PDB-wide survey of small proteins (4-6 kDa) to understand the similarities of defensins with other small disulfide-rich proteins. We found no differences when we compared defensins with non-defensins regarding the proportion and exposition to the solvent of apolar, polar, and charged residues. Then we divided all small proteins (4-6 kDa) deposited in PDB into two groups, one group with at least one disulfide bond (bonded, defensins included) and another group without any disulfide bond (unbonded). The group of bonded proteins presented apolar residues more exposed to the solvent than the unbonded group. The ab initio algorithm for tertiary protein structure prediction Robetta was more accurate to predict unbonded than bonded proteins. Our work highlights one more layer of complexity for the tertiary protein prediction structure: small disulfide-rich proteins’ ability to fold even with a poor hydrophobic core.
Preliminary report on SARS-CoV-2 Spike mutation T478K

Several SARS-CoV-2 variants have emerged, posing a renewed threat to COVID-19 containment and to vaccine and drug efficacy. In this study, we analyzed more than 1,000,000 SARS-CoV-2 genomic sequences deposited up to April 27, 2021 on the GISAID public repository, and identified a novel T478K mutation located on the SARS-CoV-2 Spike protein. The mutation is structurally located in the region of interaction with human receptor ACE2 and was detected in 11,435 distinct cases. We show that T478K has appeared and risen in frequency since January 2021, predominantly in Mexico and USA, but we could also detect it in several European countries.