Miracle-dz/UniFAR-FTUs huggingface dataset:
How to build a water-splitting machine: structural insights into photosystem II assembly

Biogenesis of photosystem II (PSII), nature’s water splitting catalyst, is assisted by auxiliary proteins that form transient complexes with PSII components to facilitate stepwise assembly events. Using cryo-electron microscopy, we solved the structure of such a PSII assembly intermediate with 2.94 Å resolution. It contains three assembly factors (Psb27, Psb28, Psb34) and provides detailed insights into their molecular function. Binding of Psb28 induces large conformational changes at the PSII acceptor side, which distort the binding pocket of the mobile quinone (QB) and replace bicarbonate with glutamate as a ligand of the non-heme iron, a structural motif found in reaction centers of non-oxygenic photosynthetic bacteria. These results reveal novel mechanisms that protect PSII from damage during biogenesis until water splitting is activated. Our structure further demonstrates how the PSII active site is prepared for the incorporation of the Mn4CaO5 cluster, which performs the unique water splitting reaction. One Sentence Highlight The high-resolution Cryo-EM structure of the photosystem II assembly intermediate PSII-I reveals how nature’s water splitting catalyst is assembled, protected and prepared for photoactivation by help of the three assembly factors Psb27, Psb28 and Psb34.
Targeting oncogenic mutations in colorectal cancer using cryptotanshinone

Colorectal cancer (CRC) is one of the most prevalent types of cancer in the world and ranks second in cancer deaths in the US. Despite the recent improvements in screening and treatment, the number of deaths associated with CRC is still very significant. The complexities involved in CRC therapy stem from multiple oncogenic mutations and crosstalk between abnormal pathways. This calls for using advanced molecular genetics to understand the underlying pathway interactions responsible for this cancer. In this paper, we construct the CRC pathway from the literature and using an existing public dataset on healthy vs tumor colon cells, we identify the genes/pathways that are mutated and are possibly responsible for the disease progression. We then introduce drugs in the CRC pathway, and using a boolean modeling technique, we deduce the drug combinations that produce maximum cell death. Our theoretical simulations demonstrate the effectiveness of Cryptotanshinone, a traditional Chinese herb derivative, achieved by targeting critical oncogenic mutations and enhancing cell death. Finally, we validate our theoretical results using wet lab experiments on HT29 and HCT116 human colorectal carcinoma cell lines.
Photodynamic antimicrobial chemotherapy, a pathway for photo-inactivation of bacteria by porphyrins compounds

Photodynamic antimicrobial chemotherapy is a pathway for consideration of cell death of many microorganisms in biology such as bacteria. Various photo-sensitizer compounds were used in this technique such as porphyrin compounds. In this work, the effect of various concentrations of cationic porphyrin compounds was investigated and compared on cell death of S. aureus and E. coli by means of a 100 watt tungsten lamp.
Essential Gene Analysis in Acinetobacter baumannii by High-Density Transposon Mutagenesis and CRISPR Interference

New approaches are urgently needed to control A. baumannii, one of the most drug-resistant pathogens known. To facilitate the development of novel targets that allow inhibition of the pathogen, we performed a large-scale identification of genes whose products the bacterium needs for growth. ABSTRACT Acinetobacter baumannii is a poorly understood bacterium capable of life-threatening infections in hospitals. Few antibiotics remain effective against this highly resistant pathogen. Development of rationally designed antimicrobials that can target A. baumannii requires improved knowledge of the proteins that carry out essential processes allowing growth of the organism. Unfortunately, studying essential genes has been challenging using traditional techniques, which usually require time-consuming recombination-based genetic manipulations. Here, we performed saturating mutagenesis with dual transposon systems to identify essential genes in A. baumannii, and we developed a CRISPR interference (CRISPRi) system for facile analysis of these genes. We show that the CRISPRi system enables efficient transcriptional silencing in A. baumannii. Using these tools, we confirmed the essentiality of the novel cell division protein AdvA and discovered a previously uncharacterized AraC family transcription factor (ACX60_RS03245) that is necessary for growth. In addition, we show that capsule biosynthesis is a conditionally essential process, with mutations in late-acting steps causing toxicity in strain ATCC 17978 that can be bypassed by blocking early-acting steps or activating the BfmRS stress response. These results open new avenues for analysis of essential pathways in A. baumannii. IMPORTANCE New approaches are urgently needed to control A. baumannii, one of the most drug-resistant pathogens known. To facilitate the development of novel targets that allow inhibition of the pathogen, we performed a large-scale identification of genes whose products the bacterium needs for growth. We also developed a CRISPR-based gene knockdown tool that operates efficiently in A. baumannii, allowing rapid analysis of these essential genes. We used these methods to define multiple processes vital to the bacterium, including a previously uncharacterized gene regulatory factor and export of a protective polymeric capsule. These tools will enhance our ability to investigate processes critical for the essential biology of this challenging hospital-acquired pathogen.
Including intraspecific trait variability to avoid distortion of functional diversity and ecological inference: lessons from natural assemblages

Functional diversity assessments are crucial and increasingly used for understanding ecological processes and managing ecosystems. The functional diversity of a community is assessed by sampling traits at one or more scales (individuals, populations, species) and calculating a summary index of the variation in trait values. However, it remains unclear how the scale at which traits are sampled and the indices used to estimate functional diversity may alter the patterns observed and inferences about ecological processes. For 40 plant and 61 ant communities, we assess functional diversity using six methods – encompassing various mean-based and probabilistic methods – chosen to reflect common scenarios where different levels of detail are available in trait data. We test whether including trait variability at different scales (from individuals to species) alter functional diversity values calculated using volume-based and dissimilarity-based indices, Functional Richness (FRic) and Rao, respectively. We further test whether such effects alter the functional diversity patterns observed across communities and their relationships with environmental drivers such as abiotic gradients and occurrences of invasive species. Intraspecific trait variability strongly determined FRic and Rao. Methods using only species’ mean trait values to calculate FRic (convex hulls) and Rao (Gower-based dissimilarity) distorted the patterns observed when intraspecific trait variability was considered. These distortions generated Type I and Type II errors for the effects of environmental factors structuring the plant and ant communities. The high sensitivity of FRic to individuals with extreme trait values was revealed in comparisons of different probabilistic methods including among-individual and among-population trait variability in functional diversity. By contrast, values and ecological patterns in Rao were consistent among methods including different scales of intraspecific trait variability. Decisions about where traits are sampled and how trait variability is included in functional diversity can drastically change the patterns observed and conclusions about ecological processes. We recommend sampling the traits of multiple individuals per species and capturing their intraspecific trait variability using probabilistic methods. We discuss how intraspecific trait variability can be reasonably estimated and included in functional diversity in the common circumstance where only limited trait data are available.
Mutational signatures in countries affected by SARS-CoV-2: Implications in host-pathogen interactome

We are in the midst of the third severe coronavirus outbreak caused by SARS-CoV-2 with unprecedented health and socio-economic consequences due to the COVID-19. Globally, the major thrust of scientific efforts has shifted to the design of potent vaccine and anti-viral candidates. Earlier genome analyses have shown global dominance of some mutations purportedly indicative of similar infectivity and transmissibility of SARS-CoV-2 worldwide. Using high-quality large dataset of 25k whole-genome sequences, we show emergence of new cluster of mutations as result of geographic evolution of SARS-CoV-2 in local population (≥10%) of different nations. Using statistical analysis, we observe that these mutations have either significantly co-occurred in globally dominant strains or have shown mutual exclusivity in other cases. These mutations potentially modulate structural stability of proteins, some of which forms part of SARS-CoV-2-human interactome. The high confidence druggable host proteins are also up-regulated during SARS-CoV-2 infection. Mutations occurring in potential hot-spot regions within likely T-cell and B-cell epitopes or in proteins as part of host-viral interactome, could hamper vaccine or drug efficacy in local population. Overall, our study provides comprehensive view of emerging geo-clonal mutations which would aid researchers to understand and develop effective countermeasures in the current crisis. Significance Our comparative analysis of globally dominant mutations and region-specific mutations in 25k SARS-CoV-2 genomes elucidates its geo-clonal evolution. We observe locally dominant mutations (co-occurring or mutually exclusive) in nations with contrasting COVID-19 mortalities per million of population) besides globally dominant ones namely, P314L (ORF1b) and D164G (S) type. We also see exclusive dominant mutations such as in Brazil (I33T in ORF6 and I292T in N protein), England (G251V in ORF3a), India (T2016K and L3606F in ORF1a) and in Spain (L84S in ORF8). The emergence of these local mutations in ORFs within SARS-CoV-2 genome could have interventional implications and also points towards their potential in modulating infectivity of SARS-CoV-2 in regional population.
Characterization of the Habitat- and Season-Independent Increase in Fungal Biomass Induced by the Invasive Giant Goldenrod and Its Impact on the Fungivorous Nematode Community

Outside its native range, the invasive plant species giant goldenrod (Solidago gigantea) has been shown to increase belowground fungal biomass. This non-obvious effect is poorly characterized; we don’t know whether it is plant developmental stage-dependent, which fractions of the fungal community are affected, and whether it is reflected in the next trophic level. To address the questions, fungal assemblages in soil samples collected from invaded and non-invaded plots in two soil types were compared. Whereas ergosterol as a marker for fungal biomass demonstrated a significant increase in fungal biomass, specific qPCR assays did not point at a quantitative shift. MiSeq-based characterization of the belowground effects of giant goldenrod revealed a local increase of mainly Cladosporiaceae and Glomeraceae. This asymmetric boost in the fungal community was reflected in a specific shift in the fungivorous nematode community. Our findings provide insight in the potential impact of invasive plants on local fungal communities.
Sequence memory in recurrent neuronal network can develop without structured input

How does spontaneous activity during development prepare cortico-cortical connections for sensory input? We here analyse the development of sequence memory, an intrinsic feature of recurrent networks that supports temporal perception. We use a recurrent neural network model with homeostatic and spike-timing-dependent plasticity (STDP). This model has been shown to learn specific sequences from structured input. We show that development even under unstructured input increases unspecific sequence memory. Moreover, networks “pre-shaped” by such unstructured input subsequently learn specific sequences faster. The key structural substrate is the emergence of strong and directed synapses due to STDP and synaptic competition. These construct self-amplifying preferential paths of activity, which can quickly encode new input sequences. Our results suggest that memory traces are not printed on a tabula rasa, but instead harness building blocks already present in the brain.
Conductance-Based Structural Brain Connectivity in Aging and Dementia

Background Structural brain connectivity has been shown to be sensitive to the changes that the brain undergoes during Alzheimer’s disease (AD) progression. Methods In this work, we use our recently proposed structural connectivity quantification measure derived from diffusion MRI, which accounts for both direct and indirect pathways, to quantify brain connectivity in dementia. We analyze data from the ADNI-2 and OASIS-3 datasets to derive relevant information for the study of the changes that the brain undergoes in AD. We also compare these datasets to the HCP dataset, as a reference. Results Our analysis shows expected trends of mean conductance with respect to age and cognitive scores, significant age prediction values in aging data, and regional effects centered among subcortical regions, and cingulate and temporal cortices. Discussion Results indicate that the conductance measure has prediction potential, especially for age, that age and cognitive scores largely overlap, and that this measure could be used to study effects such as anti-correlation in structural connections. Impact statement This work presents a methodology and a set of analyses that open new possibilities in the study of healthy and pathological aging. The methodology used here is sensitive to direct and indirect pathways in deriving brain connectivity measures from dMRI, and therefore provides information that many state-of-the-art methods do not account for. As a result, this technique may provide the research community with ways to detect subtle effects of healthy aging and AD.
MicroRNA775 Promotes Intrinsic Leaf Size and Reduces Cell Wall Pectin Level via a Target Galactosyltransferase in Arabidopsis

Plants possess unique primary cell walls made of complex polysaccharides that play critical roles in determining intrinsic cell and organ size. How genes responsible for synthesizing and modifying the polysaccharides are regulated by microRNAs (miRNAs) to control plant size remains largely unexplored. Here we identified 23 putative cell wall related miRNAs, termed CW-miRNAs, in Arabidopsis thaliana and characterized miR775 as an example. We showed that miR775 post-transcriptionally silences GALT9, which encodes an endomembrane-located galactosyltransferase belonging to the glycosyltransferase 31 family. Over-expression of miR775 and deletion of GALT9 significantly enlarged leaf-related organs, primarily owing to increases in cell size. Monosaccharide quantification, confocal Raman imaging, and immunolabelling combined with atomic force microscopy (AFM) revealed that the MIR775A-GALT9 circuit modulates pectin level and elastic modulus of the cell wall. We further showed that MIR775A is directly repressed by the transcription factor ELONGATED HYPOCOTYL 5 (HY5). Genetic analysis confirmed that HY5 is a negative regulator of leaf size and acts through the HY5-MIR775A-GALT9 repression cascade to control pectin level. These results demonstrate that miR775-regulated cell wall remodeling is an integral determinant for intrinsic leaf size in A. thaliana and highlight the need to study other CW-miRNAs for more insights into cell wall biology.
Endozoochory by parrotfish replenishes reefs with coral-associated microbiome

Parrotfish are a keystone group that reduces competition between algae and corals while shaping the dynamics and resilience of coral reefs. We investigated the structure of disseminated coral-associated bacteria and the extent to which the cell integrity of dinoflagellate photosymbionts (family Symbiodiniaceae) is maintained in the faeces. Similar levels of structural integrity and photosynthetic health of Symbidiodinaceae cells were found in both faeces and reef sediments. Besides, the sediments microbiome echoes the parrotfish faecal microbiome by sharing high diversity and a similar bacterial community composition. These findings uncover the role of excavator parrotfish endozoochory in enriching environmental reservoirs, especially reef sediments, with coral-associated bacteria and photosynthetic microalgae. These processes reinforce the coral microbiome and facilitate coral symbiont acquisition, key features critical to maintaining the health of the most threatened ecosystems on earth. Excavator parrotfish are comparable to herbivorous seed dispersers in terrestrial ecosystems based on the same endozoochorous strategy.
SARS-CoV-2 protein Nsp1 alters actomyosin cytoskeleton and phenocopies arrhythmogenic cardiomyopathy-related PKP2 mutant

Mutations in desmosomal Plakophilin-2 (PKP2) are the most prevalent drivers of arrhythmogenic cardiomyopathy (ACM) and a common cause of sudden cardiac death in young athletes. However, partner proteins that elucidate PKP2 cellular mechanism to understand cardiac dysfunction in ACM are mostly unknown. Here we identify the actin-based motor proteins Myh9 and Myh10 as key PKP2 interactors, and demonstrate that the expression of the ACM-related PKP2 mutant R735X alters actin fiber organization and cell mechanical stiffness. We also show that SARS-CoV-2 Nsp1 protein acts similarly to this known pathogenic R735X mutant, altering the actomyosin component distribution on cardiac cells. Our data reveal that the viral Nsp1 hijacks PKP2 into the cytoplasm and mimics the effect of delocalized R735X mutant. These results demonstrate that cytoplasmic PKP2, wildtype or mutant, induces the collapse of the actomyosin network, since shRNA-PKP2 knockdown maintains the cell structure, validating a critical role of PKP2 localization in the regulation of actomyosin architecture. The fact that Nsp1 and PKP2 mutant R735X share similar phenotypes also suggests that direct SARS-CoV-2 heart infection could induce a transient ACM-like disease in COVID-19 patients, which may contribute to right ventricle dysfunction, observed in patients with poor survival prognosis. Highlights The specific cardiac isoform Plakophilin-2a (PKP2) interacts with Myh9 and Myh10. PKP2 delocalization alters actomyosin cytoskeleton component organization. SARS-CoV-2 Nsp1 protein hijacks PKP2 from the desmosome into the soluble fraction where it is downregulated. Viral Nsp1 collapses the actomyosin cytoskeleton and phenocopies the arrhythmogenic cardiomyopathy-related mutant R735X.
Description, measurement, and automatic classification of the Plasmodium berghei oocyst morphology during early differentiation

After colonization of the mosquito midgut by the malaria parasite, Plasmodium differentiates from an invasive, motile ookinete to a multiplicative, sessile oocyst. Despite their importance in establishing the infection and increasing its population, the morphological transformation associated with these changes in function has been scarcely explored. Oocyst differentiation begins with the formation of a spherical protrusion near the center of the crescent-shaped ookinete. As this protuberance grows, it engulfs the content of the two distal ends, thus rounding the cell. In this work, scrutinized observations of the overall changes in shape, coupled with the migration of the malaria pigment granules and the nucleus into the protuberance, revealed that the movement of the cell content happens in an anteroposterior manner. The resulting data, formalized as morphometric measurements, led to the identification of 5 transitional stages and to the development of a computer training algorithm that automatically classifies them. Since cell differentiation has been associated with redox fluctuations, the classification algorithm was tested with parasites stained with a glutathione-specific fluorescent probe, revealing a redox modulation during differentiation.
Local circuit allowing hypothalamic control of hippocampal area CA2 activity and consequences for CA1

The hippocampus is critical for memory formation. The hypothalamic supramammillary nucleus (SuM) sends long-range projections to hippocampal area CA2. While the SuM-CA2 connection is critical for social memory, how this input acts on the local circuit is unknown. We found that SuM axon stimulation elicited mixed excitatory and inhibitory responses in area CA2 pyramidal neurons (PNs). We found that parvalbumin-expressing basket cells as responsible for the feedforward inhibitory drive of SuM over area CA2. Inhibition recruited by the SuM input onto CA2 PNs increased the precision of action potential firing both in conditions of low and high cholinergic tone. Furthermore, SuM stimulation in area CA2 modulates CA1 activity, indicating that synchronized CA2 output drives a pulsed inhibition in area CA1. Hence, the network revealed here lays basis for understanding how SuM activity directly acts on the local hippocampal circuit to allow social memory encoding.
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome

Deciphering the language of non-coding DNA is one of the fundamental problems in genome research. Gene regulatory code is highly complex due to the existence of polysemy and distant semantic relationship, which previous informatics methods often fail to capture especially in data-scarce scenarios. To address this challenge, we developed a novel pre-trained bidirectional encoder representation, named DNABERT, that forms global and transferrable understanding of genomic DNA sequences based on up and downstream nucleotide contexts. We show that the single pre-trained transformers model can simultaneously achieve state-of-the-art performance on many sequence predictions tasks, after easy fine-tuning using small task-specific data. Further, DNABERT enables direct visualization of nucleotide-level importance and semantic relationship within input sequences for better interpretability and accurate identification of conserved sequence motifs and functional genetic variants. Finally, we demonstrate that pre-trained DNABERT with human genome can even be readily applied to other organisms with exceptional performance.
Improving the Accuracy of Spectrum-based Fault Localization for Automated Program Repair

The sufficiency of test cases is essential for spectrum-based fault localization (in short, SBFL). If a given set of test cases is not sufficient, SBFL does not work. In such a case, we can improve the reliability of SBFL by adding new test cases. However, adding many test cases without considering their properties is not appropriate in the context of automated program repair (in short, APR). For example, in the case of GenProg, which is the most famous APR tool, all the test cases related to the bug module are executed for each of the mutated programs. Execution results of test cases are used for checking whether they pass all the test cases and inferring faulty statements for a given bug. Thus, in the context of APR, it is important to add necessary minimum test cases to improve the accuracy of SBFL. In this paper, we propose three strategies for selecting some test cases from a large number of automatically-generated test cases. We conducted a small experiment on bug dataset Defect4J and confirmed that the accuracy of SBFL was improved for 56.3% of target bugs while the accuracy was decreased for 17.3% in the case of the best strategy. We also confirmed that the increase of the execution time was suppressed to 1.5 seconds at the median.