Search for: All records

Nontrivial geometry of electronic Bloch states gives rise to topological insulators which are robust against sufficiently weak randomness inevitably present in any quantum material. However, increasing disorder triggers a quantum phase transition into a featureless normal insulator. As the underlying quantum critical point is approached from the topological side, small scattered droplets of normal insulators start to develop in the system and their coherent nucleation causes ultimate condensation into a trivial insulator. Unless disorder is too strong, the normal insulator accommodates disjoint tiny topological puddles. Furthermore, in the close vicinity of such a transition the emergent islands of topological and trivial insulators display spatial fractal structures, a feature that is revealed only by local topological markers. Here, we showcase this (possibly) generic phenomenon that should be apposite to dirty topological crystals of any symmetry class in any dimension from the Bott index and local Chern marker for a square-lattice-based disordered Chern insulator model. 

Abstract Regulatory networks coordinate metabolism to control how plants adapt to biotic and abiotic stresses. This coordination can align transcriptional shifts across metabolic pathways using cis-regulatory elements shared across the enzyme genes within these pathways. While the role of transcription factors (TFs) in controlling this process across pathways is well known, less is known regarding the role of shared cis-regulatory elements across the genes in a pathway. Sharing cis-regulatory elements across the genes in an enzyme complex or pathway, can create coordinated regulation of the pathway by a TF. However, it is unclear if all the genes in a pathway or enzyme complex need to be fully coordinated for maximal function. For example, if one gene in an enzyme complex loses a cis-regulatory element, it may not alter the function of the enzyme complexes function if post-transcriptional or compensatory transcriptional changes are sufficient to balance the complex. To test how cis-modular membership shapes the function of an enzyme complex, we used CRISPR/Cas9 to abolish a common cis-regulatory element across the promoters of nine genes required for the mitochondrial pyruvate dehydrogenase complex (mtPDC). This complex is composed of three apoenzymes and is a central hub coordinating carbon flow between glycolysis and the tricarboxylic acid (TCA) cycle. Different combinations of these cis-element mutations were tested across the genes in the complex inArabidopsis thalianaand the created genotypes were phenotyped for altered enzyme function using digital growth analysis, disease assays, metabolomics, and transcriptomics. This analysis revealed that mutating cis-element motifs of genes in this enzyme complex produced distinct phenotypes, displaying promoter-specific buffering and modularity. 

A series of 1,3,5,7-tetraphenyl-aza-BODIPY dyes functionalized with electron-donating or withdrawing groups at the para-positions of the phenyl rings on either the 1,7- or 3,5-positions were synthesized and characterized. The electron-donating group selected was –NH2, while the electron-withdrawing groups spanned a range of strengths, from strong (-NO2) to moderate (-NH3+) and mild (-Ndouble bondCdouble bondS). The structural modifications were strategically implemented to investigate their impact on the dyes photophysical properties. Spectroscopic studies revealed that these dyes exhibit intense absorption and emission in the near-infrared (NIR) region (678–855 nm). The photophysical properties, including molar absorptivity, fluorescence quantum yield, and Stokes shift were found to depend significantly on both the electronic nature (donating/withdrawing) and positioning (1,7- vs. 3,5-) of the substituents. Complementary computational studies provided insights into the electronic structures and excited-state dynamics, corroborating experimental observations. Time-dependent density functional theory (TD-DFT) calculations revealed that the electron density distribution and the frontier orbitals’ energies and shapes were significantly influenced by the electronic effects of the substituent groups. This study underscores the tunability of aza-BODIPY dyes through rational molecular design, enabling precise control over their optical properties for tailored NIR applications. 

Orthopoxviruses (OPVs), including the causative agents of smallpox and mpox have led to devastating outbreaks in human populations worldwide. However, the discontinuation of smallpox vaccination, which also provides cross-protection against related OPVs, has diminished global immunity to OPVs more broadly. We apply machine learning models incorporating both host ecological and viral genomic features to predict likely reservoirs of OPVs.Wedemonstrate that incorporating viral genomic features in addition to host ecological traits enhanced the accuracy of potential OPV host predictions, highlighting the importance of host-virus molecular interactions in predicting potential host species. We identify hotspots for geographic regions rich with potential OPV hosts in parts of southeast Asia, equatorial Africa, and the Amazon, revealing high overlap between regions predicted to have a high number of potential OPV host species and those with the lowest smallpox vaccination coverage, indicating a heightened risk for the emergence or establishment of zoonotic OPVs. Our findings can be used to target wildlife surveillance, particularly related to concerns about mpox establishment beyond its historical range. 

Abstract Arabidopsis thaliana (hereafter Arabidopsis) is a small plant with a fast generation time and a well-annotated genome, which makes it ideal for research labs. It is arguably the most used model species in basic plant sciences. Over the past half century, studies in Arabidopsis have generated enormous insight into fundamental principles of plant life, ranging from mechanistic molecular biology to the complexities of interacting ecosystems. Based on research in Arabidopsis, we now understand that while basic cellular metabolism is generally conserved across species, variation in specialized metabolite enzymes gives rise to complex bouquets of chemical weapons that are tightly interwoven with the environment. Understanding how these are produced, regulated, and—especially—how they are deployed remains a key research area for plant immunity. The breadth of work in Arabidopsis provides a unique window into this complicated aspect of life as a plant. We are happy to have an opportunity to share our common interest in these aspects in this review. Due to space constraints, we focus on compounds produced by Arabidopsis with demonstrated antimicrobial properties. We hope that this focus (despite our eagerness to write more) will inspire new avenues of research that will contribute to a more complete understanding of immunity. 

Abstract Data reduction methods are frequently employed in large genomics and phenomics studies to extract core patterns, reduce dimensionality, and alleviate multiple testing effects. Principal component analysis (PCA), in particular, identifies the components that capture the most variance within omics datasets. While data reduction can simplify complex datasets, it remains unclear how the use of PCA impacts downstream analyses such as quantitative trait loci (QTL) or genome-wide association (GWA) approaches and their biological interpretation. In QTL studies, an alternative to data reduction is the use of post-hoc data summarization approaches, such as hotspot analysis, which involves mapping individual traits and consolidating results based on shared genomic locations. To evaluate how different analytical approaches may alter the biological insights derived from multi-dimensional QTL datasets, we compared individual trait hotspots with PCA-based QTL mapping using transcriptomic and metabolomic data from a structured recombinant inbred line population. Interestingly, these two approaches identified different genomic regions and genetic architectures. These findings suggest that mapping PCA-reduced data does not merely streamline analyses but may generate a fundamentally different view of the underlying genetic architecture compared to individual trait mapping and hotspot analysis. Thus, the use of PCA and other data reduction techniques prior to QTL or GWAS mapping should be carefully considered to ensure alignment with the specific biological question being addressed. 

Hydrothermal circulation at mid-ocean ridges drives the exchange of heat and matter from Earth’s interior to the global ocean and supports deep-sea life. Away from the ridge axis, however, the spatial extent of hydrothermal discharge remains enigmatic. Using near-bottom data for a 25-kilometer-long section of the East Pacific Rise between 9°43′N and 9°57′N, we show that considerable hydrothermal flow occurs at variable distances from the ridge axis. Mapping the seafloor and water column along this segment using an autonomous underwater vehicle, we identified 448 candidate hydrothermal chimneys. More than half of them lie outside the axial summit trough, indicating that hydrothermal fluids discharge over a larger area than previously thought. Water column measurements show that >27% of mapped constructs are likely to be venting actively. Our results indicate that widespread active hydrothermal flow occurs over the near-axis region, with important implications for constraining total heat flux along mid-ocean ridges and for identifying previously unexplored benthic habitats.