[E.E.G. sequences of deep hypothermia].
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Electroencephalography↗
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Diagnostic and phylogenetic perspectives of the 2023 Murray Valley encephalitis virus outbreak in Australia: an observational study.
BACKGROUND: An outbreak of Murray Valley encephalitis virus (MVEV), the largest since 1974, was observed in Australia between Jan 1 and July 31, 2023. This study aims to characterise the utility of diagnostic platforms, testing algorithms, and genomic characteristics of MVEV to facilitate a comprehensive framework for MVEV testing and surveillance in the outbreak setting. METHODS: In this observational study, we assessed flavivirus diagnostics for all patients with suspected Murray Valley encephalitis in Australia from Jan 1 to July 31, 2023. We included all patients with confirmed Murray Valley encephalitis, probable Murray Valley encephalitis, or acute unspecified flavivirus infection using the Communicable Diseases Network Australia case definition. Cases were excluded if an alternative diagnosis was identified. We collected blood, serum, cerebrospinal fluid, brain tissue, urine, or a combination of these samples, as appropriate and at the discretion of the treating clinician. We conducted multimodal diagnostic testing, which included flavivirus-specific serological and nucleic acid amplification testing. Metagenomic next-generation sequencing, including next-generation deep sequencing, target-enrichment, and targeted amplification, was conducted on human and representative mosquito-derived samples obtained from established mosquito population surveillance programmes for phylogenetic analysis. FINDINGS: 27 patients with encephalitis were assessed for MVEV between Jan 1, 2023, and July 31, 2023, 23 (85%) of whom fulfilled national case definitions for confirmed Murray Valley encephalitis. Patient ages ranged from 6 weeks to 83 years (median 62·0 years [IQR 31·0-67·5]) and patients were mostly male (21 [78%] male patients and six [22%] female patients). Incidence varied widely by geographical region and was highest in the Northern Territory (32·0 per 1 000 000 population). Diagnostic specimen collection generally occurred promptly (median 6·0 days [IQR 4·0-14·5] from symptom onset to diagnostic specimen collection). In seven patients, case assignation relied on convalescent serum samples to assess for seroconversion or an appropriate rise in antibody titre (to four times the initial value or greater), or both. MVEV-specific IgM was detectable in serum samples of 17 (81%) of 21 patients tested by day 7 and MVEV IgG or total antibody (TAb) were detected in 18 (100%) of 18 patients tested by day 30. MVEV-specific IgM (or TAb) and MVEV RNA were detected in cerebrospinal fluid collected within 14 days of symptom onset in nine (39%) of 23 patients and seven (28%) of 25 patients, respectively. Phylogenetic analysis revealed two circulating MVEV genotypes, G1A and G2, in mosquitoes and humans in 2023. In southeast Australia, only G1A was detected and probably introduced from enzootic foci in northern Australia. INTERPRETATION: This study provides a comprehensive overview of the diagnostic workflows and phylogenetic evaluations used during the 2023 MVEV outbreak in Australia, emphasising the importance of a multimodal approach for accurate and timely confirmation of flavivirus infection. Further One Health surveillance for MVEV and other zoonotic flaviviruses is key, given potential expanded ecological niches in the context of episodic climatic events. FUNDING: None.
Humans↗
Blood mitochondrial heteroplasmic variants and cognitive performance in late midlife: REGARDS study.
BACKGROUND: Studies linking mitochondrial DNA (mtDNA) variants to cognition yielded inconsistent findings, and the underlying mechanisms remain unclear. We investigated whether mtDNA heteroplasmic variants were associated with cognitive outcomes, including the Montreal Cognitive Assessment (MoCA), in 197 late midlife adults from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort with complete data. METHODS: MtDNA was sequenced from blood using targeted deep sequencing. Adjusted linear and mixed-effects models examined the associations by functional regions, genes, total variant burden, nonsynonymous variants, and control regions. RESULTS: Heteroplasmic variants in the control region (β = -0.44, 95% CI: -0.83, -0.05, p = 0.027) and transfer RNA (tRNA) genes (β = -1.34, 95% CI: -2.58, -0.11, p = 0.034) were associated with MoCA baseline scores. Individual variants in cytochrome c oxidase subunit 1 (CO1) (β = -1.51, 95% CI: -2.54, -0.47, p = 0.005), NADH dehydrogenase subunit 1 (ND1) (β = -2.63, 95% CI: -4.56, -0.70, p = 0.008), and Displacement Loop (D-LOOP2) (β = -2.25, 95% CI: -4.20, -0.30, p = 0.025) was associated with reduced baseline MoCA scores. The ND6 (β = −1.23, 95% CI: −2.09, − 0.37, p = 0.006), ND4 (β = −1.11, 95% CI: −2.02, − 0.20, p = 0.018), ATP Synthase Membrane Subunit 8 (ATP8; β = −1.38, 95% CI: −2.63, − 0.13, p = 0.031), and D-LOOP1 (β = −0.61, 95% CI: −1.20, − 0.01, p = 0.045) genes suggested a potential association with executive function. Longitudinal Animal Fluency Test (AFT) scores were inversely associated with heteroplasmic variants in coding regions (β = -0.10, 95% CI: -0.19, -0.006, p = 0.049), the total number of variants (β = -0.06, 95% CI: -0.11, -0.003, p = 0.037) and total nonsynonymous variants (β = -0.11, 95% CI: -0.21, -0.01, p = 0.040). Variants in the control region were associated with the greatest decline in verbal fluency (β = −0.20, 95% CI: −0.39 to − 0.002, p = 0.049). No associations were observed between mitochondrial variants and verbal memory performance or the MoCA composite scores. CONCLUSIONS: Our study indicates that mitochondrial variants measured in blood may provide insight into cognitive function during midlife. However, additional studies are needed to validate these associations and to address potential power limitations in our study.
Humans↗
A paradoxical population structure of var DBLα types in Africa.
The var multigene family encodes Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1), central to host-parasite interactions. Genome structure studies have identified three major groups of var genes by specific upstream sequences (upsA, B, or C). Var with these ups groups have different chromosomal locations, transcriptional directions, and associations with disease severity. Here we explore temporal and spatial diversity of a region of var genes encoding the DBLα domain of PfEMP1 in Africa. By applying a novel ups classification algorithm (cUps) to publicly-available DBLα sequence datasets, we categorised DBLα according to association with the three ups groups, thereby avoiding the need to sequence complete genes. Data from deep sequencing of DBLα types in a local population in northern Ghana surveyed seven times from 2012 to 2017 found variants with rare-to-moderate-to-extreme frequencies, and the common variants were temporally stable in this local endemic area. Furthermore, we observed that every isolate repertoire, whether mono- or multiclonal, comprised DBLα types occurring with these frequency ranges implying a common genome structure. When comparing African countries of Ghana, Gabon, Malawi, and Uganda, we report that some DBLα types were consistently found at high frequencies in multiple African countries while others were common only at the country level. The implication of these local and pan-Africa population patterns is discussed in terms of advantage to the parasite with regards to within-host adaptation and resilience to malaria control.
Plasmodium falciparum↗
Multiomics approaches reveal direct NF-κB p65 target genes in pancreatic islets during cytokine exposure and in type 1 diabetes.
Autoimmune diseases, including Type 1 diabetes (T1D), are often characterized by overactive inflammatory signaling pathways. The proinflammatory cytokine interleukin-1β (IL-1β) elicits global gene expression changes in islet β-cells which overlap with islets obtained from human donors with T1D. The direct transcriptional link between NF-κB subunit p65 and target genes involved with autoimmune events was investigated. We used a multiomics approach including bulk RNA-sequencing (RNA-Seq), single-cell RNA-sequencing (scRNA-Seq), and chromatin immunoprecipitation coupled to deep sequencing (ChIP-Seq), alongside molecular docking simulations, and transcriptional assays. Through the various experimental modalities, we identified early response genes driven by IL-1β that were differentially expressed in pancreatic islets from human T1D donors and also conserved across mouse, rat, and human tissues. ChIP-Seq revealed genes that are direct genomic targets of the NF-κB p65 transcription factor. Moreover, regions that gained RNA polymerase II binding following cellular exposure to IL-1β were identified, complementing the early response gene profile induced by β-cell exposure to IL-1β. Molecular docking simulations predicted that mutations reducing p65 transcriptional capacity do not alter DNA binding ability. These findings clearly show that IL-1β signaling in pancreatic β-cells directs p65 to specific genomic regions congruent with increased gene expression relevant to T1D in β-cell lines as well as mouse and human islets exposed to cytokines. Islets from human donors with T1D express genes identified as direct p65 targets using unbiased approaches, implicating heightened NF-κB activity as a critical component of autoimmune disease etiology.NEW & NOTEWORTHY Using multiple Seq-based approaches, this study identified genes expressed in human pancreatic tissue from donors with Type 1 diabetes that are regulated acutely by exposure to the cytokine interleukin-1beta. The NF-kB transcription factor p65 (RelA) was determined via ChIP-Seq to be a major control node regulating this immediate early response. These collective datasets are consistent with a paradigm of overactive NF-kB signaling as a critical component of autoimmunity in both rodents and humans.
Humans↗
Genome-wide identification of human functional DNA using a neutral indel model.
It has become clear that a large proportion of functional DNA in the human genome does not code for protein. Identification of this non-coding functional sequence using comparative approaches is proving difficult and has previously been thought to require deep sequencing of multiple vertebrates. Here we introduce a new model and comparative method that, instead of nucleotide substitutions, uses the evolutionary imprint of insertions and deletions (indels) to infer the past consequences of selection. The model predicts the distribution of indels under neutrality, and shows an excellent fit to human-mouse ancestral repeat data. Across the genome, many unusually long ungapped regions are detected that are unaccounted for by the neutral model, and which we predict to be highly enriched in functional DNA that has been subject to purifying selection with respect to indels. We use the model to determine the proportion under indel-purifying selection to be between 2.56% and 3.25% of human euchromatin. Since annotated protein-coding genes comprise only 1.2% of euchromatin, these results lend further weight to the proposition that more than half the functional complement of the human genome is non-protein-coding. The method is surprisingly powerful at identifying selected sequence using only two or three mammalian genomes. Applying the method to the human, mouse, and dog genomes, we identify 90 Mb of human sequence under indel-purifying selection, at a predicted 10% false-discovery rate and 75% sensitivity. As expected, most of the identified sequence represents unannotated material, while the recovered proportions of known protein-coding and microRNA genes closely match the predicted sensitivity of the method. The method's high sensitivity to functional sequence such as microRNAs suggest that as yet unannotated microRNA genes are enriched among the sequences identified. Furthermore, its independence of substitutions allowed us to identify sequence that has been subject to heterogeneous selection, that is, sequence subject to both positive selection with respect to substitutions and purifying selection with respect to indels. The ability to identify elements under heterogeneous selection enables, for the first time, the genome-wide investigation of positive selection on functional elements other than protein-coding genes.
Animals↗
Absolute copy number aware CNV calling of sub-megabase segments in ultra-low coverage single-cell DNA sequencing data.
Recent advances in ultra-low coverage whole-genome sequencing (WGS) of single cells have enabled detailed analysis of copy number variation at a throughput approaching that of single-cell RNA sequencing. However, downstream computational methods have not seen comparable advances and are largely adaptations of deep sequencing methodology with reduced precision. Here, we present ASCENT, a computational method built to take full advantage of modern direct tagmentation-based WGS at ultra-low depth. Using joint segmentation with high-resolution bins, we accurately detect small segments, achieving accurate copy number profiles even at 100 000 reads per cell. ASCENT implements true absolute copy state inference for single cells, based on statistical modeling of coverage rather than comparison to a reference, while taking variable segment copy state into account. Further, ASCENT implements per-segment copy-neutral loss of heterozygosity (LOH) calling without the need for non-tumor or bulk WGS reference. When applied to a pediatric B-ALL sample, ASCENT finds copy-neutral LOH in a small segment and a minor subclone defined by breakpoints missed in bulk WGS. Thus, by applying appropriate computational methods, single-cell WGS provides clear advantages over bulk, even at a relatively low cell number and sequencing depth.
DNA Copy Number Variations↗
Sequence evaluation of four pooled-tissue normalized bovine cDNA libraries and construction of a gene index for cattle.
An essential component of functional genomics studies is the sequence of DNA expressed in tissues of interest. To provide a resource of bovine-specific expressed sequence data and facilitate this powerful approach in cattle research, four normalized cDNA libraries were produced and arrayed for high-throughput sequencing. The libraries were made with RNA pooled from multiple tissues to increase efficiency of normalization and maximize the number of independent genes for which sequence data were obtained. Target tissues included those with highest likelihood to have impact on production parameters of animal health, growth, reproductive efficiency, and carcass merit. Success of normalization and inter- and intralibrary redundancy were assessed by collecting 6000-23,000 sequences from each of the libraries (68,520 total sequences deposited in GenBank). Sequence comparison and assembly of these sequences was performed in combination with 56,500 other bovine EST sequences present in the GenBank dbEST database to construct a cattle Gene Index (available from The Institute for Genomic Research at http://www.tigr.org/tdb/tgi.shtml). The 124,381 bovine ESTs present in GenBank at the time of the analysis form 16,740 assemblies that are listed and annotated on the Web site. Analysis of individual library sequence data indicates that the pooled-tissue approach was highly effective in preparing libraries for efficient deep sequencing.
Animals↗
Sharp genetic break between Atlantic and English Channel populations of the polychaete Pectinaria koreni, along the North coast of France.
This study uses enzymatic and mitochondrial genes to infer the relative importance of historical processes and contemporary hydrodynamic features on the observed patterns of genetic structure in subdivided populations of Pectinaria koreni (Polychaeta: Pectinariidae) along the coasts of Brittany and the English Channel. Nucleotide sequence variation of a 603-bp fragment of the mtDNA cytochrome oxidase subunit I gene revealed a surprisingly deep phylogeographic break of about 16% divergence separating the Brittany and Channel populations, which coincides with a biogeographic boundary along the western coast of Brittany. Deep sequence divergence with fixed haplotype differences and the inversion of allele frequencies at two enzyme loci suggests the occurrence of potential cryptic or sibling species of P. koreni. The two clades showed opposite features. Channel populations exhibited bimodal match-mismatch curves due to two highly divergent haplotypes occurring at high frequencies and no overall heterozygote deficiencies at enzyme loci, suggesting respectively, a historic secondary contact between two differentiated populations followed by contemporary panmixia. On the contrary, Brittany populations displayed unimodal curves with low nucleotide diversity and highly significant heterozygote deficiencies, probably reminiscent of a recent population expansion and recolonisation of Brittany with contemporary admixture of divergent populations.
Animals↗
Sequence optimization targeting mRNA stability enhances monoclonal antibody titers in CHO cells.
This study presents a DNA sequence optimization approach that integrates mRNA stability as a tunable design parameter to enhance monoclonal antibody expression in Chinese hamster ovary (CHO) cells. A comprehensive combinatorial library of synonymous coding-sequence variants of an IgG1 light chain was integrated as single copies at a defined genomic locus in CHO cells with identical regulatory elements. Steady-state mRNA abundance, quantified by deep sequencing of gDNA and mRNA, served as a proxy for mRNA stability. These data were used to train a machine learning model that predicts mRNA abundance from coding sequence using embeddings from a pre-trained nucleotide transformer. This abundance predictor, together with established translational metrics, was incorporated into a genetic algorithm for multi-objective codon optimization. As proof-of-concept, we optimized sequences encoding Trastuzumab to either maximize or minimize the abundance criterion and obtained benchmark sequences from two commercial providers. Using targeted integration, we generated CHO cell lines and measured protein titer and cell-specific productivity. Sequences optimized for high abundance significantly increased intracellular mRNA levels (+41%), protein titer (+59%), and cell-specific productivity (+85%) relative to low-abundance designs, while viable cell densities remained comparable. Compared to commercial benchmarks, high-abundance sequences achieved significantly higher titer (+70%) and cell-specific productivity (+98%). These findings establish mRNA stability as a practical and complementary design parameter for codon optimization in monoclonal antibody production, with potential applicability to other proteins and expression systems.
CHO↗
Mitochondrial versus nuclear gene sequences in deep-level mammalian phylogeny reconstruction.
Both mitochondrial and nuclear gene sequences have been employed in efforts to reconstruct deep-level phylogenetic relationships. A fundamental question in molecular systematics concerns the efficacy of different types of sequences in recovering clades at different taxonomic levels. We compared the performance of four mitochondrial data sets (cytochrome b, cytochrome oxidase II, NADH dehydrogenase subunit I, 12S rRNA-tRNA-16S rRNA) and eight nuclear data sets (exonic regions of alpha-2B adrenergic receptor, aquaporin, ss-casein, gamma-fibrinogen, interphotoreceptor retinoid binding protein, kappa-casein, protamine, von Willebrand Factor) in recovering deep-level mammalian clades. We employed parsimony and minimum-evolution with a variety of distance corrections for superimposed substitutions. In 32 different pairwise comparisons between these mitochondrial and nuclear data sets, we used the maximum set of overlapping taxa. In each case, the variable-length bootstrap was used to resample at the size of the smaller data set. The nuclear exons consistently performed better than mitochondrial protein and rRNA-tRNA coding genes on a per-residue basis in recovering benchmark clades. We also concatenated nuclear genes for overlapping taxa and made comparisons with concatenated mitochondrial protein-coding genes from complete mitochondrial genomes. The variable-length bootstrap was used to score the recovery of benchmark clades as a function of the number of resampled base pairs. In every case, the nuclear concatenations were more efficient than the mitochondrial concatenations in recovering benchmark clades. Among genes included in our study, the nuclear genes were much less affected by superimposed substitutions. Nuclear genes having appropriate rates of substitution should receive strong consideration in efforts to reconstruct deep-level phylogenetic relationships.
Animals↗
Gene discovery and annotation using LCM-454 transcriptome sequencing.
454 DNA sequencing technology achieves significant throughput relative to traditional approaches. More than 261,000 ESTs were generated by 454 Life Sciences from cDNA isolated using laser capture microdissection (LCM) from the developmentally important shoot apical meristem (SAM) of maize (Zea mays L.). This single sequencing run annotated >25,000 maize genomic sequences and also captured approximately 400 expressed transcripts for which homologous sequences have not yet been identified in other species. Approximately 70% of the ESTs generated in this study had not been captured during a previous EST project conducted using a cDNA library constructed from hand-dissected apex tissue that is highly enriched for SAMs. In addition, at least 30% of the 454-ESTs do not align to any of the approximately 648,000 extant maize ESTs using conservative alignment criteria. These results indicate that the combination of LCM and the deep sequencing possible with 454 technology enriches for SAM transcripts not present in current EST collections. RT-PCR was used to validate the expression of 27 genes whose expression had been detected in the SAM via LCM-454 technology, but that lacked orthologs in GenBank. Significantly, transcripts from approximately 74% (20/27) of these validated SAM-expressed "orphans" were not detected in meristem-rich immature ears. We conclude that the coupling of LCM and 454 sequencing technologies facilitates the discovery of rare, possibly cell-type-specific transcripts.
Base Sequence↗
ZILA-SRM: a probabilistic framework with zero-inflated latent models for robust strain reconstruction from metagenomes.
UNLABELLED: Resolving bacterial strain diversity from shotgun metagenomic data is fundamental to understanding intra-host evolution, transmission dynamics, and phenotypic heterogeneity. However, current probabilistic approaches face a severe "identifiability limit" when disentangling highly similar genomes. Under high-noise conditions, sequencing errors, coverage overdispersion, and collinearity confound standard expectation-maximization algorithms, resulting in overfitting and spurious "ghost" strains. Here, we introduce zero-inflated latent allocation for strain reconstruction from metagenomes with adaptive sparsity regularization (ZILA-SRM) to overcome this barrier through three innovations. First, we integrate a zero-inflated Poisson mixture model to decouple "structural zeros" (true strain absence) from "sampling zeros" (stochastic dropout), addressing overdispersion in standard Poisson-based tools. Second, we impose a convex adaptive sparsity regularization penalty that leverages biological sparsity priors to shrink noise artifacts dynamically. Third, we implement a graph-theoretic refinement step using maximal clique enumeration to resolve haplotype collinearity. Benchmarking against StrainFinder and MixtureS on 702 synthetic data sets shows that ZILA-SRM achieves a 20% improvement in precision in high-complexity scenarios while maintaining over 80% recall for minor variants at 0.5% abundance. Re-analysis of deep-sequencing data from 195 Mycobacterium tuberculosis clinical samples reveals cryptic low-abundance drug-resistant variants in 12% of patients, including a minor clone carrying the rpoB S450L mutation. Furthermore, application to skin microbiome data sets further reveals a strong negative correlation between dominant Staphylococcus aureus and Staphylococcus epidermidis strains, providing genomic evidence for competitive exclusion. These findings establish ZILA-SRM as a robust tool for resolving strain-level diversity in complex metagenomes. IMPORTANCE: Understanding microbial communities at the strain level is critical because closely related strains can differ dramatically in traits such as drug resistance, virulence, and ecological interactions. However, resolving individual strains from metagenomic sequencing data remains difficult, especially when strains are highly similar or present at low abundance. As a result, biologically meaningful diversity is often obscured or misinterpreted as noise. In this study, we introduce a new framework that improves the reliability of strain reconstruction from complex metagenomic data. By reducing false-positive strain detection while preserving sensitivity to rare variants, our approach enables more accurate characterization of microbial populations. This improved resolution reveals previously hidden subpopulations in clinical and microbiome datasets, providing clearer insights into microbial evolution, competition, and the emergence of clinically relevant traits such as antibiotic resistance.
Metagenomics↗
MicroRNAs and other small RNAs enriched in the Arabidopsis RNA-dependent RNA polymerase-2 mutant.
The Arabidopsis genome contains a highly complex and abundant population of small RNAs, and many of the endogenous siRNAs are dependent on RNA-Dependent RNA Polymerase 2 (RDR2) for their biogenesis. By analyzing an rdr2 loss-of-function mutant using two different parallel sequencing technologies, MPSS and 454, we characterized the complement of miRNAs expressed in Arabidopsis inflorescence to considerable depth. Nearly all known miRNAs were enriched in this mutant and we identified 13 new miRNAs, all of which were relatively low abundance and constitute new families. Trans-acting siRNAs (ta-siRNAs) were even more highly enriched. Computational and gel blot analyses suggested that the minimal number of miRNAs in Arabidopsis is approximately 155. The size profile of small RNAs in rdr2 reflected enrichment of 21-nt miRNAs and other classes of siRNAs like ta-siRNAs, and a significant reduction in 24-nt heterochromatic siRNAs. Other classes of small RNAs were found to be RDR2-independent, particularly those derived from long inverted repeats and a subset of tandem repeats. The small RNA populations in other Arabidopsis small RNA biogenesis mutants were also examined; a dcl2/3/4 triple mutant showed a similar pattern to rdr2, whereas dcl1-7 and rdr6 showed reductions in miRNAs and ta-siRNAs consistent with their activities in the biogenesis of these types of small RNAs. Deep sequencing of mutants provides a genetic approach for the dissection and characterization of diverse small RNA populations and the identification of low abundance miRNAs.
Arabidopsis↗
Histone H3 lysine K4 methylation and its role in learning and memory.
Epigenetic modifications such as histone methylation permit change in chromatin structure without accompanying change in the underlying genomic sequence. A number of studies in animal models have shown that dysregulation of various components of the epigenetic machinery causes cognitive deficits at the behavioral level, suggesting that proper epigenetic control is necessary for the fundamental processes of learning and memory. Histone H3 lysine K4 (H3K4) methylation comprises one component of such epigenetic control, and global levels of this mark are increased in the hippocampus during memory formation. Modifiers of H3K4 methylation are needed for memory formation, shown through animal studies, and many of the same modifiers are mutated in human cognitive diseases. Indeed, all of the known H3K4 methyltransferases and four of the known six H3K4 demethylases have been associated with impaired cognition in a neurologic or psychiatric disorder. Cognitive impairment in such patients often manifests as intellectual disability, consistent with a role for H3K4 methylation in learning and memory. As a modification quintessentially, but not exclusively, associated with transcriptional activity, H3K4 methylation provides unique insights into the regulatory complexity of writing, reading, and erasing chromatin marks within an activated neuron. The following review will discuss H3K4 methylation and connect it to transcriptional events required for learning and memory within the developed nervous system. This will include an initial discussion of the most recent advances in the developing methodology to analyze H3K4 methylation, namely mass spectrometry and deep sequencing, as well as how these methods can be applied to more deeply understand the biology of this mark in the brain. We will then introduce the core enzymatic machinery mediating addition and removal of H3K4 methylation marks and the resulting epigenetic signatures of these marks throughout the neuronal genome. We next foray into the brain, discussing changes in H3K4 methylation marks within the hippocampus during memory formation and retrieval, as well as the behavioral correlates of H3K4 methyltransferase deficiency in this region. Finally, we discuss the human cognitive diseases connected to each H3K4 methylation modulator and summarize advances in developing drugs to target them.
Animals↗
ChIP-Rx: Arabidopsis Chromatin Profiling Using Quantitative ChIP-Seq.
Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) is widely used to probe the chromatin landscape of transcription factors, chromatin components, and associated proteins. Conventional ChIP normalization procedures robustly allow estimating differences in local enrichment across genomic regions. Yet, inter-sample comparisons can be biased by technical variability and biological differences. This is notably the case when samples display large differences in the abundance of the target protein or its enrichment at chromatin. For example, epigenome defects are improperly detected or quantified upon large-effect genetic or chemical inhibition of chromatin modifiers. To circumvent these caveats and robustly determine biological variations while minimizing technical variability, ChIP adaptations using an external reference have flourished. Here, we describe a step-by-step protocol employing a reference exogenous chromatin (ChIP-Rx) that allows absolute comparisons of epigenome variations in Arabidopsis samples displaying drastic differences in chromatin mark abundance. In contrast to the originally published ChIP-Rx approach, which assumes that exogenous spike-in references are constant across samples, the method detailed here involves the sequencing of each input sample to account for technical variability in initial reference chromatin contents. We also report a detailed computational workflow with an accompanying Github resource to help in calculating spike-in normalization factors, applying them to normalize epigenome tracks, and performing spike-in normalized inter-sample differential analyses. We propose two ways of computing the spike-in factor: a classically used method based on raw counts and a noise-corrected method using peak detection on the exogenous genome.
Arabidopsis↗
Collateral sensitivity-harnessing microbial vulnerabilities as a solution to antimicrobial resistance.
Bacteria exhibit an evolutionary trade-off through their development of collateral sensitivity (CS) which allows them to resist one antibiotic while becoming more vulnerable to another. This vulnerability offers a compelling therapeutic opportunity by selecting against resistant isolates. Laboratory evolution studies, genome sequencing, deep mutagenesis and use of artificial intelligence and machine learning can design the bespoke strategy against multi-drug-resistant bacteria. This review discusses about recent studies that are rationally designed to harness this evolutionary trade-off for the development of alternative antimicrobial strategies. The translational barriers to the clinical implementation of CS are addressed and evidence-based design principles for optimization of CS-guided therapy are discussed.
Bacteria↗
Identification of genetic determinants that promote biofilm growth under heterotrophic conditions in Cupriavidus necator using transposon enrichment.
Cupriavidus necator is a metabolically versatile β-proteobacterium of growing interest for auto- and heterotrophic bioprocesses, yet the genetic determinants governing its biofilm formation remain largely uncharacterized, particularly under process-relevant heterotrophic conditions. Here, we applied a forward-genetics transposon-enrichment approach to identify loci which promote surface-associated growth. A high-density mini-Tn5 mutant library (26,185 insertion clones, exceeding the >17,000 required for genome-wide coverage) was cultivated as a biofilm in a microfluidic flow-cell system on fructose for 168 h, and the surface-associated community was characterized by deep sequencing. Twelve genes showed significantly elevated insertion frequencies, several with documented links to biofilm formation in other bacteria, including the ferrous-iron uptake system (feoA/feoB), galU, and a GSDEF/EAL dual-domain protein. The gene B2043 (E6A55_RS29530), encoding this c-di-GMP-metabolizing protein, was selected for validation by markerless deletion. Under static conditions, the ΔB2043 mutant showed a 1.69 ± 0.06-fold increase in biofilm-associated biomass (p = 5.16 × 10-15). Under flow-through conditions, the mutant attached faster, entered exponential growth ∼10 h earlier, reached its biovolume plateau ∼16 h earlier than the wild-type, and formed distinct tower-like structures. These results identify B2043 as a negative regulator of biofilm formation acting predominantly during attachment, provide the first experimental evidence for c-di-GMP-dependent biofilm regulation in C. necator H16, and establish a functional-genomics framework - together with eleven further candidate loci - for engineering productive biofilms in this organism.
Biofilm formation↗