Biology subjects

Frank, M.

Publications and source records attributed to Frank, M..

At least 55 records · Page 3Linked to original sources

bioRxiv2021

Evolution of Human-specific Alleles Protecting Cognitive Function of Grandmothers

Late-onset Alzheimers Disease (LOAD) pathology is rare in our closest living evolutionary relatives (chimpanzees), which also express much lower microglial levels of CD33(Siglec-3)-a myelomonocytic receptor inhibiting innate immune reactivity by extracellular V-set domain recognition of sialic acid(Sia)-containing "self-associated molecular patterns" (SAMPs). We earlier showed that V-set domain-deficient CD33-variant allele, protective against LOAD, is derived and specific to hominin-lineage. We now report that CD33 also harbors multiple hominin-specific V-set domain mutations and explore selection forces that may have favored such genomic changes. N-glycolylneuraminic acid (Neu5Gc), the preferred Sia-ligand of ancestral CD33 is absent in humans, due to hominin-specific, fixed loss-of-function mutation in CMAH, which generates CMP-Neu5Gc from its precursor, CMP-N-acetylneuraminic acid (Neu5Ac). Extensive mutational analysis and MD-simulations indicate that fixed change in amino acid 21 of hominin V-set domain and conformational changes related to His45 corrected for Neu5Gc-loss by switching to Neu5Ac-recognition. Considering immune-evasive "molecular mimicry" of SAMPs by pathogens, we found that human-specific pathogens Neisseria gonorrhoeae and Group B Streptococcus (affecting fertility and fetuses/neonates respectively) selectively bind huCD33 and this binding is significantly impacted by amino acid 21 modification. Alongside LOAD-protective CD33 alleles, humans harbor additional, derived, population-universal, cognition-protective variants absent in "great ape" genomes. Interestingly, 11 of 13 SNPs in these human genes (including CD33), that protect the cognitive health of elderly populations, are not shared by genomes of archaic hominins: Neanderthals and Denisovans. Finally, we present a plausible evolutionary scenario to compile, correlate and comprehend existing knowledge about huCD33 evolution and suggest that grandmothering emerged in humans.

evolutionary biology↗

bioRxiv2021

The Evolutionary History of Small RNAs in the Solanaceae

The Solanaceae or "nightshade" family is an economically important group that harbors a remarkable amount of diversity. To gain a better understanding of how the unique biology of the Solanaceae relates to the familys small RNA genomic landscape, we downloaded over 255 publicly available small RNA datasets that comprise over 2.6 billion reads of sequence data. We applied a suite of computational tools to predict and annotate two major small RNA classes: (1) microRNAs (miRNAs), typically 20-22 nt RNAs generated from a hairpin precursor and functioning in gene silencing, and (2) short interfering RNAs (siRNAs), including 24-nt heterochromatic siRNAs (hc-siRNAs) typically functioning to repress repetitive regions of the genome via RNA-directed DNA methylation, as well as secondary phased siRNAs (phasiRNAs) and trans-acting siRNAs (tasiRNAs) generated via miRNA-directed cleavage of a Pol II-derived RNA precursor. Our analyses described thousands of small RNA loci, including poorly-understood clusters of 22-nt siRNAs that accumulate during viral infection. The birth, death, expansion, and contraction of these small RNA loci are dynamic evolutionary processes that characterize the Solanaceae family. These analyses indicate that individuals within the same genus share similar small RNA landscapes, whereas comparisons between distinct genera within the Solanaceae reveal relatively few commonalities. ONE-SENTENCE SUMMARYWe use over 255 publicly-available small RNA datasets to characterize the small RNA landscape for the Solanaceae family.

plant biology↗

bioRxiv2021

Dynamic Interactions of Fully Glycosylated SARS-CoV-2 Spike Protein with Various Antibodies

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a public health crisis, and the vaccines that can induce highly potent neutralizing antibodies are essential for ending the pandemic. The spike (S) protein on the viral envelope mediates human angiotensin-converting enzyme 2 (ACE2) binding and thus is the target of a variety of neutralizing antibodies. In this work, we built various S trimer-antibody complex structures on the basis of the fully glycosylated S protein models described in our previous work, and performed all-atom molecular dynamics simulations to get insight into the structural dynamics and interactions between S protein and antibodies. Investigation of the residues critical for S-antibody binding allows us to predict the potential influence of mutations in SARS-CoV-2 variants. Comparison of the glycan conformations between S-only and S-antibody systems reveals the roles of glycans in S-antibody binding. In addition, we explored the antibody binding modes, and the influences of antibody on the motion of S protein receptor binding domains. Overall, our analyses provide a better understanding of S-antibody interactions, and the simulation-based S-antibody interaction maps could be used to predict the influences of S mutation on S-antibody interactions, which will be useful for the development of vaccine and antibody-based therapy.

biophysics↗

bioRxiv2021

The transcriptomic landscape of the photoperiodic stress response in Arabidopsis thaliana resembles the response to pathogen infection.

Plants are exposed to regular diurnal rhythms of light and dark. Changes in the photoperiod by the prolongation of the light period cause photoperiod stress in short day-adapted Arabidopsis thaliana. Here we report on the transcriptional response to photoperiod stress of wild-type A. thaliana and photoperiod stress-sensitive cytokinin signalling and clock mutants. Transcriptomic changes induced by photoperiod stress included numerous changes in reactive oxygen (ROS)-related transcripts and showed a strong overlap with changes occurring in response to ozone stress and pathogen attack, which have in common the induction of an apoplastic oxidative burst. A core set of photoperiod stress-responsive genes has been identified, including salicylic acid (SA) biosynthesis and signalling genes. Genetic analysis revealed a central role for NPR1 in the photoperiod stress response as npr1-1 mutants were stress-insensitive. Photoperiod stress treatment led to a strong increase in camalexin levels which is consistent with shared photoperiod stress and pathogen response pathways. Photoperiod stress induced resistance of Arabidopsis plants to a subsequent infection by Pseudomonas syringae cv. tomato DC3000 indicating priming of the defence response. Together, photoperiod stress causes transcriptional reprogramming resembling plant pathogen defence responses and induces systemic acquired resistance in the absence of a pathogen. One sentence summaryPhotoperiod stress results in significant dynamic transcriptomic changes related to oxidative stress similar to those caused by pathogen attack and primes the defence response against a subsequent pathogen infection.

plant biology↗

bioRxiv2021

Site-specific steric control of SARS-CoV-2 spike glycosylation

A central tenet in the design of vaccines is the display of native-like antigens in the elicitation of protective immunity. The abundance of N-linked glycans across the SARS-CoV-2 spike protein is a potential source of heterogeneity between the many different vaccine candidates under investigation. Here, we investigate the glycosylation of recombinant SARS-CoV-2 spike proteins from five different laboratories and compare them against infectious virus S protein. We find patterns which are conserved across all samples and this can be associated with site-specific stalling of glycan maturation which act as a highly sensitive reporter of protein structure. Molecular dynamics (MD) simulations of a fully glycosylated spike support s a model of steric restrictions that shape enzymatic processing of the glycans. These results suggest that recombinant spike-based SARS-CoV-2 immunogen glycosylation reproducibly recapitulates signatures of viral glycosylation.

biochemistry↗

bioRxiv2021

Gene regulatory networks for compatible versus incompatible grafts identify a role for SlWOX4 during junction formation

Graft incompatibility is a poorly understood phenomenon that presents a serious agricultural challenge. Unlike immediate incompatibility that results in rapid death, delayed incompatibility can take months or even years to manifest, creating a significant economic burden for perennial crop production. To gain insight into the genetic mechanisms underlying this phenomenon, we developed a model system with Solanum lycopersicum tomato and Capsicum annuum pepper heterografting, which expresses signs of anatomical junction failure within the first week of grafting. By generating a detailed timeline for junction formation we were able to pinpoint the cellular basis for this delayed incompatibility. Furthermore, we infer gene regulatory networks for compatible self-grafts versus incompatible heterografts based on these key anatomical events, which predict core regulators for grafting. Finally, we delve into the role of vascular development in graft formation and validate SlWOX4 as a regulator for grafting in tomato. Notably, SlWOX4 is the first gene to be functionally implicated in vegetable crop grafting.

plant biology↗

bioRxiv2021

Site-specific O-glycosylation analysis of SARS-CoV-2 spike protein produced in insect and human cells

Enveloped viruses hijack not only the host translation processes, but also its glycosylation machinery, and to a variable extent cover viral surface proteins with tolerogenic host-like structures. SARS-CoV-2 surface protein S presents as a trimer on the viral surface and is covered by a dense shield of N-linked glycans, and a few O-glycosites have been reported. The location of O-glycans is controlled by a large family of initiating enzymes with variable expression in cells and tissues and hence difficult to predict. Here, we used our well-established O-glycoproteomic workflows to map the precise positions of O-linked glycosylation sites on three different entities of protein S - insect cell or human cell-produced ectodomains, or insect cell derived receptor binding domain (RBD). In total 25 O-glycosites were identified, with similar patterns in the two ectodomains of different cell origin, and a distinct pattern of the monomeric RBD. Strikingly, 16 out of 25 O-glycosites were located within three amino acids from known N-glycosites. However, O-glycosylation was primarily found on peptides that were unoccupied by N-glycans, and otherwise had low overall occupancy. This suggests possible complementary functions of O-glycans in immune shielding and negligible effects of O-glycosylation on subunit vaccine design for SARS-CoV-2.

molecular biology↗

bioRxiv2021

Quantitative dissection of color patterning in the foliar ornamental Coleus reveals underlying features driving aesthetic value

O_LIColeus is a popular ornamental plant that exhibits a diverse array of foliar color patterns. New cultivars are currently hand selected by both amateur and experienced plant breeders. In this study, we reimagine coleus breeding using a quantitative color analysis framework. C_LIO_LIDespite impressive advances in high-throughput data collection and processing, complex color patterns remain challenging to extract from image datasets. Using a new phenotyping approach called "ColourQuant," we extract and analyze pigmentation patterns from one of the largest coleus breeding populations in the world. C_LIO_LIWorking with this massive dataset, we are able to analyze quantitative relationships between maternal plants and their progeny, identify features that underlie breeder-selections, and collect and compare consumer input on trait preferences. C_LIO_LIThis study is one of the most comprehensive explorations into complex color patterning in plant biology and provides new insights and tools for exploring the color pallet of the plant kingdom. C_LI

plant biology↗

bioRxiv2020

Systematic detection of functional proteoform groups from bottom-up proteomic datasets

The cellular proteome, the ensemble of proteins derived from a genome, catalyzes and controls thousands of biochemical functions that are the basis of living cells. Whereas the protein coding regions of the genome of the human and many other species are well known, the complexity and composition of proteomes largely remains to be explored. This task is challenging because mechanisms including alternative splicing and post-translational modifications generally give rise to multiple distinct, but related proteins - proteoforms - per coding gene that expand the functional capacity of a cell. Bottom-up proteomics is a mass spectrometric method that infers the identity and quantity of proteins from the measurement of peptides derived from these proteins by proteolytic digestion. Whereas bottom-up proteomics has become the method of choice for the detection of translation products from essentially any gene, the inherent missing link between measured peptides and their parental proteins has so far precluded the systematic assessment of proteoforms and thus limited the resolution of proteome maps. Here we present a novel, data-driven strategy to assign peptides to unique functional proteoform groups based on peptide correlation patterns across large bottom-up proteomic datasets. Our strategy does not fully characterize specific proteoforms, as is achievable in top-down approaches. Rather, it clusters peptides into functional proteoform groups that are directly linked to the biological context of the study. This allows the detection of tens to hundreds of proteoform groups in an untargeted fashion from bottom-up proteomics experiments. We applied the strategy to two types of bottom-up proteomic datasets. The first is a protein complex co-fractionation dataset where native complexes across two different cell cycle stages were resolved and analyzed. Here, our approach enabled the systematic detection and evaluation of assembly specific proteoforms at an unprecedented scale. The second is a protein abundance vs. sample data matrix typical for bottom-up cohort studies consisting of tissue samples from the mouse BXD genetic reference panel. In either data type the method detected state-specific proteoform groups that could be linked to distinct molecular mechanisms including proteolytic cleavage, alternative splicing and phosphorylation. We envision that the presented approach lays the foundation for a systematic assessment of proteoforms and their functional implications directly from bottom-up proteomic datasets.

systems biology↗

bioRxiv2020

Direct Observation of the Mechanism of Antibiotic Resistance by Mix-and-Inject at the European XFEL

In this study, we follow the diffusion and buildup of occupancy of the substrate ceftriaxone in M. tuberculosis {beta}-lactamase BlaC microcrystals by structural analysis of the enzyme substrate complex at single millisecond time resolution. We also show the binding and the reaction of an inhibitor, sulbactam, on a slower millisecond time scale. We use the mix-and-inject technique to initiate these reactions by diffusion, and determine the resulting structures by serial crystallography using ultrafast, intense X-ray pulses from the European XFEL (EuXFEL) arriving at MHz repetition rates. Here, we show how to use the EuXFEL pulse structure to dramatically increase the size of the data set and thereby the quality and time resolution of "molecular movies" which unravel ligand binding and enzymatically catalyzed reactions. This shows the great potential for the EuXFEL as a tool for biomedically relevant research, particularly, as shown here, for investigating bacterial antibiotic resistance. One Sentence SummaryDirect observation of fast ligand binding in a biomedically relevant enzyme at near atomic resolution with MHz X-ray pulses at the European XFEL.

biophysics↗

bioRxiv2020

Likelihood Approximation Networks (LANs) for Fast Inference of Simulation Models in Cognitive Neuroscience

In cognitive neuroscience, computational modeling can formally adjudicate between theories and affords quantitative fits to behavioral/brain data. Pragmatically, however, the space of plausible generative models considered is dramatically limited by the set of models with known likelihood functions. For many models, the lack of a closed-form likelihood typically impedes Bayesian inference methods. As a result, standard models are evaluated for convenience, even when other models might be superior. Likelihood-free methods exist but are limited by their computational cost or their restriction to particular inference scenarios. Here, we propose neural networks that learn approximate likelihoods for arbitrary generative models, allowing fast posterior sampling with only a one-off cost for model simulations that is amortized for future inference. We show that these methods can accurately recover posterior parameter distributions for a variety of neurocognitive process models. We provide code allowing users to deploy these methods for arbitrary hierarchical model instantiations without further training.

neuroscience↗

bioRxiv2020

Structure, Dynamics, Receptor Binding, and Antibody Binding of Fully-glycosylated Full-length SARS-CoV-2 Spike Protein in a Viral Membrane

The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mediates host cell entry by binding to angiotensin-converting enzyme 2 (ACE2), and is considered the major target for drug and vaccine development. We previously built fully-glycosylated full-length SARS-CoV-2 S protein models in a viral membrane including both open and closed conformations of receptor binding domain (RBD) and different templates for the stalk region. In this work, multiple s-long all-atom molecular dynamics simulations were performed to provide deeper insight into the structure and dynamics of S protein, and glycan functions. Our simulations reveal that the highly flexible stalk is composed of two independent joints and most probable S protein orientations are competent for ACE2 binding. We identify multiple glycans stabilizing the open and/or closed states of RBD, and demonstrate that the exposure of antibody epitopes can be captured by detailed antibody-glycan clash analysis instead of a commonly-used accessible surface area analysis that tends to overestimate the impact of glycan shielding and neglect possible detailed interactions between glycan and antibody. Overall, our observations offer structural and dynamic insight into SARS-CoV-2 S protein and potentialize for guiding the design of effective antiviral therapeutics.

biophysics↗

bioRxiv2020

A novel isoform of ACE2 is expressed in human nasal and bronchial respiratory epithelia and is upregulated in response to RNA respiratory virus infection

Angiotensin-converting enzyme 2 (ACE2) is the main entry point in the airways for SARS-CoV-2. ACE2 binding to SARS-CoV-2 protein Spike triggers viral fusion with the cell membrane, resulting in viral RNA genome delivery into the host. Despite ACE2s critical role in SARS-CoV-2 infection, an understanding of ACE2 expression, including in response to viral infection, remains unclear. Until now ACE2 was thought to encode five transcripts and one 805 amino acid protein. Here we identify a novel short isoform of ACE2. Short ACE2 is expressed in the airway epithelium, the main site of SARS-CoV-2 infection; it is substantially upregulated in response to interferon stimulation and RV infection, but not in response to SARS-CoV-2 infection, and it shows differential regulation in asthma patients. This short isoform lacks SARS-CoV-2 spike glycoprotein high-affinity binding sites and altogether, our data are consistent with a model where short ACE2 may influence host susceptibility to SARS-CoV-2 infection.

molecular biology↗

bioRxiv2020

Unsupervised Neural Network Models of the Ventral Visual Stream

Deep neural networks currently provide the best quantitative models of the response patterns of neurons throughout the primate ventral visual stream. However, such networks have remained implausible as a model of the development of the ventral stream, in part because they are trained with supervised methods requiring many more labels than are accessible to infants during development. Here, we report that recent rapid progress in unsupervised learning has largely closed this gap. We find that neural network models learned with deep unsupervised contrastive embedding methods achieve neural prediction accuracy in multiple ventral visual cortical areas that equals or exceeds that of models derived using todays best supervised methods, and that the mapping of these neural network models hidden layers is neuroanatomically consistent across the ventral stream. Moreover, we find that these methods produce brain-like representations even when trained on noisy and limited data measured from real childrens developmental experience. We also find that semi-supervised deep contrastive embeddings can leverage small numbers of labelled examples to produce representations with substantially improved error-pattern consistency to human behavior. Taken together, these results suggest that deep contrastive embedding objectives may be a biologically-plausible computational theory of primate visual development.

neuroscience↗

bioRxiv2020

Vein-to-blade ratio is an allometric indicator of climate-induced changes in grapevine leaf size and shape

PremiseAs a leaf expands, its shape dynamically changes. Previously, we documented an allometric relationship between vein and blade area in grapevine leaves. Larger leaves have a smaller ratio of primary and secondary vein area relative to blade area compared to smaller leaves. We sought to use allometry as an indicator of leaf size to measure the environmental effects of climate on grapevine leaf morphology. MethodsWe measure the ratio of vein-to-blade area in 8,412 leaves from the same 208 vines across four growing seasons (2013, 2015, 2016, and 2017) using 21 homologous landmarks. Matching leaves by vine and node, we correlate size and shape of grapevine leaves with climate variables. Key resultsVein-to-blade ratio varies strongly between years in ways that blade or vein area do not. Maximum daily temperature and to a lesser degree precipitation are the most strongly correlated climate variables with vein-to-blade ratio, indicating that smaller leaves are associated with heat waves and drought. Leaf count and overall leaf area of shoots and the vineyard population studied also diminish with heat and drought. Grapevine leaf primordia initiate in buds the year prior to when they emerge, and we find that climate during the previous growing season exerts the largest statistical effects over these relationships. ConclusionsOur results demonstrate the profound effects of heat and drought on the vegetative morphology of grapevines and show that vein-to-blade ratio is a strong allometric indicator of the effects of climate on grapevine leaf morphology.

plant biology↗

bioRxiv2020

Root-derived trans-zeatin cytokinin protects Arabidopsis plants against photoperiod stress

Recently, a novel type of abiotic stress caused by a prolongation of the light period - coined photoperiod stress - has been described in Arabidopsis. During the night after the prolongation of the light period, stress and cell death marker genes are induced. The next day, strongly stressed plants display a reduced photosynthetic efficiency and leaf cells eventually enter programmed cell death. The phytohormone cytokinin (CK) acts as a negative regulator of this photoperiod stress syndrome. In this study, we show that Arabidopsis wild-type plants increase the CK concentration in response to photoperiod stress. Analysis of cytokinin synthesis and transport mutants revealed that root-derived trans-zeatin (tZ)-type CKs protect against photoperiod stress. The CK signaling proteins ARABIDOPSIS HISTIDINE PHOSPHOTRANSFER PROTEIN 2 (AHP2), AHP3 and AHP5 and transcription factors ARABIDOPSIS RESPONSE REGULATOR 2 (ARR2), ARR10 and ARR12 are required for the protective activity of CK. Analysis of higher order B-type arr mutants suggested that a complex regulatory circuit exists in which the loss of ARR10 or ARR12 can rescue the arr2 phenotype. Together the results revealed the role of root-derived CK acting in the shoot through the two-component signaling system to protect from the negative consequences of strong photoperiod stress.

plant biology↗

bioRxiv2019

Acclimation, priming and memory in the response of Arabidopsis thaliana seedlings to cold stress

Because stress experiences are often recurrent plants have developed strategies to remember a first so-called priming stress to eventually respond more effectively to a second triggering stress. Here, we have studied the impact of discontinuous or sustained cold stress (4 {degrees}C) on in vitro grown Arabidopsis thaliana seedlings of different age and their ability to get primed and respond differently to a later triggering stress. Cold treatment of 7-d-old seedlings induced the expression of cold response genes but did not cause a significantly enhanced freezing resistance. The competence to increase the freezing resistance in response to cold was associated with the formation of true leaves. Discontinuous exposure to cold only during the night led to a stepwise modest increase in freezing tolerance provided that the intermittent phase at ambient temperature was less than 32 h. Seedlings exposed to sustained cold treatment developed a higher freezing tolerance which was further increased in response to a triggering stress during three days after the priming treatment had ended indicating cold memory. Interestingly, in all scenarios the primed state was lost as soon as the freezing tolerance had reached the level of naive plants indicating that an effective memory was associated with an altered physiological state. Known mutants of the cold stress response (cbfs, erf105) and heat stress memory (fgt1) did not show an altered behaviour indicating that their roles do not extend to memory of cold stress.

plant biology↗

bioRxiv2019

Parallel accumulation - serial fragmentation combined with data-independent acquisition (diaPASEF): Bottom-up proteomics with near optimal ion usage

Data independent acquisition (DIA) modes isolate and concurrently fragment populations of different precursors by cycling through segments of a predefined precursor m/z range. Although these selection windows collectively cover the entire m/z range, overall only a few percent of all incoming ions are sampled. Making use of the correlation of molecular weight and ion mobility in a trapped ion mobility device (timsTOF Pro), we here devise a novel scan mode that samples up to 100% of the peptide precursor ion current. We extend an established targeted data extraction workflow by including the ion mobility dimension for both signal extraction and scoring, thereby increasing the specificity for precursor identification. Data acquired from whole proteome digests and mixed organism samples demonstrate deep proteome coverage and a very high degree of reproducibility as well as quantitative accuracy, even from 10 ng sample amounts.

systems biology↗