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bioRxiv2020

Effects of spectral light quality on the growth, productivity, and elemental ratios in differently pigmented marine phytoplankton species

Effects of light quality on the growth, productivity, and cellular composition of three uniquely pigmented marine phytoplankton species were characterized. To accomplish this, cultures of Prochlorococcus marinus, Synechococcus sp., and Thalassiosira weissflogii were grown under three commercially available LEDs as well as a fluorescent growth light. Despite having equal photosynthetically active radiation, light quality and thus photosynthetically usable radiation differed between the treatments. Growth was unaffected in all species tested, yet primary productivity was affected in P. marinus and Synechococcus sp. All species regulated cellular carbon and nitrogen quotas as a direct response to light spectra, while cellular chlorophyll a was regulated in Synechococcus sp. and T. weissflogii only. Analysis of pigment ratios revealed minor acclimations in some of the cultures and photophysiological analysis indicated changes in the photoacclimation state between different light environments. These results show that while the species used in our experiment are able to maintain growth when exposed to lights of varying quality, underlying cellular metabolism and biochemistry can be affected. The data presented here highlight the importance of carefully choosing a lighting environment with a defined spectral quality when designing laboratory-based experiments or setting up bioreactors for biomass generation. HighlightWith light emitting diode-based growth lights becoming available to researchers, it is important to consider the spectral quality of light when designing experiments to understand responses of phytoplankton to environmental conditions.

plant biology↗

bioRxiv2020

Procentriole microtubules as drivers of centriole reduplication

Centriole reduplication leads to the formation of supernumerary centrosomes, which promote cellular transformation, invasion and are a hallmark of tumors. A close association between a mother centriole and a procentriole (engagement), established during centriole duplication, intrinsically blocks reduplication. Premature loss of centriole association predisposes centrioles for reduplication and occurs during various types of cell cycle arrests in the presence of high Polo-like kinase 1 activity. Here we use nano-scale imaging and biochemistry to reveal the processes leading to the loss of centriole association and reduplication. We discover that centriole reduplication is driven by events occurring on procentriole microtubule walls. These events are mechanistically different from mitotic centriole separation driven by Pericentrin and Separase but are similar to the physiological process of centriole distancing occurring in unperturbed cycling G2 cells. We propose a concept in which centriole reduplication is a consequence of hijacked and amplified centriole maturation process. HighlightsO_LISeparase-mediated Pericentrin reorganization is not required for centriole distancing and reduplication in interphase. C_LIO_LIExpression of active Plk1 in S phase leads to centrosomal ultrastructural changes resembling G2 phase. C_LIO_LIProcentrioles without microtubule walls cannot disengage. C_LIO_LICentriole distancing is intrinsically regulated by the events occurring on procentriole microtubules. C_LI

cell biology↗

bioRxiv2020

CDK1 controls CHMP7-dependent nuclear envelope reformation

Through membrane sealing and disassembly of spindle microtubules, the Endosomal Sorting Complex Required for Transport-III (ESCRT-III) machinery has emerged as a key player in the regeneration of a sealed nuclear envelope (NE) during mitotic exit, and in the repair of this organelle during interphase rupture. ESCRT-III assembly at the NE occurs transiently during mitotic exit and is initiated when CHMP7, an ER-localised ESCRT-II/ESCRT-III hybrid protein, interacts with the Inner Nuclear Membrane (INM) protein LEM2. Whilst classical nucleocytoplasmic transport mechanisms have been proposed to separate LEM2 and CHMP7 during interphase, it is unclear how CHMP7 assembly is suppressed in mitosis when NE and ER identities are mixed. Here, we use live cell imaging and protein biochemistry to examine the biology of these proteins during mitotic exit. Firstly, we show that CHMP7 plays an important role in the dissolution of LEM2 clusters that form at the NE during M-exit. Secondly, we show that CDK1 phosphorylates CHMP7 upon mitotic entry at Ser3 and Ser441 and that this phosphorylation suppresses CHMP7s interaction with LEM2, limiting its assembly during M-phase. We show that spatiotemporal differences in the dephosphorylation of CHMP7 license its assembly at the NE during telophase, but restrict its assembly on the ER at this time. Without CDK1 phosphorylation, CHMP7 undergoes inappropriate assembly in the peripheral ER during M-exit, capturing LEM2 and downstream ESCRT-III components. Lastly, we establish that a microtubule network is dispensable for ESCRT-III assembly at the reforming nuclear envelope. These data identify a key cell-cycle control programme allowing ESCRT-III-dependent nuclear regeneration.

cell biology↗

bioRxiv2020

Label-free single-instance protein detection in vitrified cells

A general method to map molecular interactions and conformational states in structurally intact cells would find wide application in biochemistry and cell biology. We used a library of images-- calculated on the basis of known structural data--as search templates to detect targets as small as the "head" domain (350 kDa) of the ribosomes small subunit in single-tilt electron cryo-micrographs by cellular high resolution template matching (cHRTM). Atomically precise position and orientation estimates reveal the conformation of individual ribosomes and enable the detection of specifically bound ligands down to 24 kDa. We show that highly head-swivelled states are likely to play a role in mRNA translocation in living cells. cHRTM outperforms cryo-electron tomography three-fold in sensitivity and completely avoids the vicissitudes of exogenous labelling.

biophysics↗

bioRxiv2020

Genome-Enabled Discovery of Anthraquinone Biosynthesis in Senna tora

Senna tora is a widely used medicinal plant. Its health benefits have been attributed to the large quantity of anthraquinones, but how they are made in plants remains a mystery. To identify the genes responsible for plant anthraquinone biosynthesis, we sequenced and annotated the genome of S. tora at the chromosome level with contig N50 and super-scaffold N50 of 4.03 Mb and 41.7 Mb. Comparison among related plant species showed that a chalcone synthase-like (CHS-L) gene family has lineage-specifically and rapidly expanded in S. tora. Combining genomics, transcriptomics, metabolomics, and biochemistry, we identified a CHS-L responsible for biosynthesis of anthraquinones, the first example in plants. The S. tora reference genome will accelerate the discovery of biologically active anthraquinone biosynthesis pathways in medicinal plants. One Sentence SummaryThe chromosome-scale reference genome of a medicinal plant Senna tora, transcriptomics, metabolomics, and biochemical analysis provide new insights into anthraquinone biosynthesis in plants.

plant biology↗

bioRxiv2020

The draft genome sequence of herbaceous diploid bamboo Raddia distichophylla

Bamboos are important non-timber forest plants widely distributed in the tropical and subtropical regions of Asia, Africa, America, and Pacific islands. They comprise the Bambusoideae in the grass family (Poaceae), including approximately 1,700 described species in 127 genera. In spite of the widespread uses of bamboo for food, construction and bioenergy, the gene repertoire of bamboo still remains largely unexplored. Raddia distichophylla (Schrad. ex Nees) Chase, belonging to the tribe Olyreae (Bambusoideae, Poaceae), is diploid herbaceous bamboo with only slightly lignified stems. In this study, we report a draft genome assembly of the approximately [~]589 Mb whole-genome sequence of R. distichophylla with a contig N50 length of 86.36 Kb. Repeated sequences account for [~]49.08% of the genome, of which LTR retrotransposons occupy [~]35.99% of whole genome. A total of 30,763 protein-coding genes were annotated in the R. distichophylla genome with an average transcript size of 2,887 bp. Access to this herbaceous bamboo genome sequence will provide novel insights into biochemistry, molecular-assisted breeding programs and germplasm conservation for bamboo species world-wide.

genomics↗

bioRxiv2020

Where in the leaf is intercellular CO2 (Ci)? Considerations and recommendations for assessing gaseous diffusion in leaves

The assumptions that water vapor exchange occurs exclusively through stomata, that the intercellular airspace is fully saturated with water vapor, and that CO2 gradients are negligible between stomata and the intercellular airspace have enabled significant advancements in photosynthetic gas exchange research for nearly 60 years via calculation of intercellular CO2 (Ci). However, available evidence suggests that these assumptions may be overused. Here we review the literature surrounding evidence for and against the assumptions made by Moss & Rawlins (1963). We reinterpret data from the literature by propagating different rates of cuticular water loss, CO2 gradients, and unsaturation through the data. We find that in general, when cuticle conductance is less than 1% of stomatal conductance, the assumption that water vapor exchange occurs exclusively through stomata has a marginal effect on gas exchange calculations, but this is not true when cuticle conductance exceeds 5% of stomatal conductance. Our analyses further suggest that CO2 and water vapor gradients have stronger impacts at higher stomatal conductance, while cuticle conductance has a greater impact at lower stomatal conductance. Therefore, we recommend directly measuring Ci whenever possible, measuring apoplastic water potentials to estimate humidity inside the leaf, and exercising caution when interpreting data under conditions of high temperature and/or low stomatal conductance, and when a species is known to have high cuticular conductance. HighlightLeaf water vapor and CO2 exchange have been successfully used to model photosynthetic biochemistry. We review critical assumptions in these models and make recommendations about which need to be re-assessed.

plant biology↗

bioRxiv2020

Impaired chloroplast positioning affects photosynthetic capacity and regulation of the central carbohydrate metabolism during cold acclimation

Photosynthesis and carbohydrate metabolism of higher plants need to be tightly regulated to prevent tissue damage during environmental changes. The intracellular position of chloroplasts changes due to a changing light regime. Chloroplast avoidance and accumulation response under high and low light, respectively, are well known phenomena, and deficiency of chloroplast movement has been shown to result in photodamage and reduced biomass accumulation. Yet, effects of chloroplast positioning on underlying metabolic regulation are less well understood. Here, we analysed photosynthesis together with metabolites and enzyme activities of the central carbohydrate metabolism during cold acclimation of the chloroplast unusual positioning 1 (chup1) mutant of Arabidopsis thaliana. We compared cold acclimation under ambient and low light and found that maximum quantum yield of PSII was significantly lower in chup1 than in Col-0 under both conditions. Our findings indicated that net CO2 assimilation in chup1 is rather limited by biochemistry than by photochemistry. Further, cold-induced dynamics of sucrose phosphate synthase differed significantly between both genotypes. Together with a reduced rate of sucrose cycling derived from kinetic model simulations our study provides evidence for a central role of chloroplast positioning for photosynthetic and metabolic acclimation to low temperature.

plant biology↗

bioRxiv2020

Metabolomic signatures of coral bleaching history

Coral bleaching, a process where corals expel their photosynthetic symbionts, has a profound impact on the health and function of coral reefs. As global ocean temperatures continue to rise, bleaching poses the greatest threat to coral reef ecosystems. Here, untargeted metabolomics was used to analyze the biochemicals in pairs of adjacent corals from a patch reef in K[a]ne ohe Bay, Hawai i, where one colony in the pair bleached (in 2015) and recovered while the other did not bleach. There was a strong metabolomic signature of prior bleaching history four years after recovery found in both the host and its algal symbionts. Machine learning analysis determined that the strongest metabolite drivers of the difference in bleaching phenotype were a group of betaine lipids. Those with saturated fatty acids were significantly enriched in thermally tolerant corals and those with longer, unsaturated and diacyl forms were enriched in historically bleached corals. Host immune response molecules, Lyso-PAF and PAF, were also altered by bleaching history and were strongly correlated with symbiont community and algal-derived metabolites suggesting a role of coral immune modulation in symbiont choice and bleaching response. To validate these findings, we tested a separate in situ set of corals and were able to predict the bleaching phenotype with 100% accuracy. Furthermore, corals subjected to an experimental temperature stress had strong phenotype-specific responses in all components of the holobiont, which served to further increase the differences between historical bleaching phenotypes. Thus, we show that natural bleaching susceptibility is simultaneously manifested in the biochemistry of the coral animal and the algal symbiont and that this bleaching history results in different physiological responses to temperature stress. This work provides insight into the biochemical mechanisms involved in coral bleaching and presents a valuable new tool for resilience-based reef restoration.

ecology↗

bioRxiv2020

Comparison of analytical methods for rapid & reliable quantification of plant-based carbohydrates for the quintessential bioenergy educator

Biochemical conversion of plant-based insoluble carbohydrate polymers, such as starch from corn grains or cellulose-hemicellulose from corn stover, into soluble fermentable sugars (e.g., glucose and xylose) for bioenergy production has seen tremendous research activity and commercial-scale biorefineries deployment over the last three decades, particularly in regions around the world that have a dominant agricultural-based economy. Therefore, educators in schools and universities have developed various hands-on experimental activities to engage the general public and students either in outreach events or lab/classroom-based settings to instruct students on various inter-disciplinary concepts relevant to bioenergy and biochemicals production. One of the limitations of most available protocols is the lack of systematic and comprehensive comparison of educator-friendly analytical tools and protocols for quantitative analysis of water-soluble carbohydrates commonly encountered in a biorefinery backdrop during the biochemical conversion of lignocellulosic biomass to biofuels/biochemicals. Here, we systematically compare and validate findings from four leading analytical approaches for detection and quantification of lignocellulosic biomass derived soluble carbohydrates. We compare these assay methods based on the overall ease of use, detection accuracy/sensitivity, commercial availability, analytical cost per assay run, and suitability for use by instructors in biorefining specific hands-on activity protocols. Next, we provide a detailed instructional protocol that utilizes one of these validated soluble sugar assays as part of a ∼90 min hands-on bioenergy focused activity (called ‘Grass-to-Gas!’) conducted at Rutgers University with pre-university high school students. ‘Grass-to-Gas!’ activity involves students running biochemical assays that helps them understand the various facets of cellulosic biomass hydrolysis by commercial cellulase enzymes and monitoring the total glucose product released using our validated sugar assays to finally estimate the fractional conversion of cellulose-to-glucose. Lastly, we further demonstrate how such carbohydrate-based analytical methods can be used by instructors to help university students explore and understand various chemistry, biochemistry, and chemical engineering concepts relevant to other advanced operations involved in lignocellulose biorefining. These activity protocols would greatly aid educators teaching interdisciplinary science and engineering concepts to students in the backdrop of lignocellulose biorefining.Competing Interest StatementThe authors have declared no competing interest.View Full Text

scientific communication and education↗

bioRxiv2020

Introducing undergraduate students to reverse genetics in the laboratory: a case study of a project-oriented learning (POL) system in Taishan Medical University, China

Biochemistry and molecular biology have become increasingly reliant on experimental experience, because they are difficult subjects to understand from a theoretical approach. The Innovation and Entrepreneurship Training Program was established by the China Ministry of Education to foster the scientific interests and experiences of undergraduate students. Here, we reported on an innovative project-oriented learning (POL) system directed by Taishan Medical University (Named Shandong First Medical University & Shandong Academy of Sciences since February 2019) China, which fused innovative project with biochemical course concepts. This study takes reverse genetics, which is considered to be difficult to understand through course-only learning, as an example. To help undergraduate students understand the principle of reverse genetics, the project involved producing hepatitis C virus in vitro. Furthermore, to give them a comprehensive scientific experience based on their knowledge from textbook, extensive mentorship was provided through the project, including theoretical guidance and technical support for experiments. Assessment showed a comprehensive improvement after participating in these programs. In conclusion, this POL system was a good model that enabled undergraduates to learn more during courses. It also provided a chance to experience hands-on sciences, which might motivate them to pursue a career in science.View Full Text

scientific communication and education↗

bioRxiv2020

Learning Peptide Recognition Rules for a Low-Specificity Protein

Many proteins interact with short linear regions of target proteins. For some proteins, however, it is difficult to identify a well-defined sequence motif that defines its target peptides. To overcome this difficulty, we used supervised machine learning to train a model that treats each peptide as a collection of easily-calculated biochemical features rather than as an amino acid sequence. As a test case, we dissected the peptide-recognition rules for human S100A5 (hA5), a low-specificity calcium binding protein. We trained a Random Forest model against a recently released, high-throughput phage display dataset collected for hA5. The model identifies hydrophobicity and shape complementarity, rather than polar contacts, as the primary determinants of peptide binding specificity in hA5. We tested this hypothesis by solving a crystal structure of hA5 and through computational docking studies of diverse peptides onto hA5. These structural studies revealed that peptides exhibit multiple binding modes at the hA5 peptide interface--all of which have few polar contacts with hA5. Finally, we used our trained model to predict new, plausible binding targets in the human proteome. This revealed a fragment of the protein -1-syntrophin binds to hA5. Our work helps better understand the biochemistry and biology of hA5, as well as demonstrating how high-throughput experiments coupled with machine learning of biochemical features can reveal the determinants of binding specificity in low-specificity proteins.

biophysics↗

bioRxiv2020

Leaf reflectance can surrogate foliar economics better than physiological traits across macrophyte species

Macrophytes are key players in aquatic ecosystems diversity, but knowledge on variability of their functional traits, among and within species, is still limited. Remote sensing is a high-throughput, feasible option for characterizing plant traits at different scales, provided that reliable spectroscopy models are calibrated with congruous empirical data. We sampled leaves from six floating and emergent macrophyte species common in temperate areas, covering different phenological stages, seasons, and environmental conditions, and measured leaf reflectance (400-2500 nm) and leaf traits (dealing with photophysiology, pigments and structure). We explored optimal spectral bands combinations and established non-parametric reflectance-based models for selected traits, eventually showing how airborne hyperspectral data can capture spatial-temporal macrophyte variability. Our key finding is that structural - leaf dry matter content, leaf mass per area - and biochemical - chlorophyll-a content and chlorophylls to carotenoids ratio - traits can be surrogated by leaf reflectance with relative error under 20% across macrophyte species, while performance of reflectance-based models for photophysiological traits depends on species. This finding shows the link between leaf reflectance and leaf economics (structure and biochemistry) for aquatic plants, thus supporting the use of remote sensing for enhancing the level of detail of macrophyte functional diversity analysis, to intra-site and intra-species scales.

ecology↗

bioRxiv2020

miR156-mediated changes in leaf composition lead to altered photosynthetic traits during vegetative phase change

SummaryPlant morphology and physiology change with growth and development. Some of these changes are due to change in plant size and some are the result of genetically programmed developmental transitions. In this study we investigate the role of the developmental transition, vegetative phase change (VPC), on morphological and photosynthetic changes.We used overexpression of miR156, the master regulator of VPC, to modulate the timing of VPC in Populus tremula x alba, Zea mays and Arabidopsis thaliana to determine its role in trait variation independent of changes in size and overall age.Here we find that juvenile and adult leaves in all three species photosynthesize at different rates and that these differences are due to phase-dependent changes in specific leaf area (SLA) and leaf N but not photosynthetic biochemistry. Further, we found juvenile leaves with high SLA were associated with better photosynthetic performance at low light levels.This study establishes a role for VPC in leaf composition and photosynthetic performance across diverse species and environments. Variation in leaf traits due to VPC are likely to provide distinct benefits under specific environments and, as a result, selection on the timing of this transition could be a mechanism for environmental adaptation.Competing Interest StatementThe authors have declared no competing interest.View Full Text

plant biology↗

bioRxiv2020

ReCodLiver0.9: Overcoming challenges in genome-scale metabolic reconstruction of a non-model species

The availability of genome sequences, annotations and knowledge of the biochemistry underlying metabolic transformations has led to the generation of metabolic network reconstructions for a wide range of organisms in bacteria, archaea, and eukaryotes. When modeled using mathematical representations, a reconstruction can simulate underlying genotype-phenotype relationships. Accordingly, genome-scale models (GEMs) can be used to predict the response of organisms to genetic and environmental variations. A bottom-up reconstruction procedure typically starts by generating a draft model from existing annotation data on a target organism. For model species, this part of the process can be straightforward, due to the abundant organism-specific biochemical data. However, the process becomes complicated for non-model less-annotated species. In this paper, we present a draft liver reconstruction, ReCodLiver0.9, of Atlantic cod (Gadus morhua), a non-model teleost fish, as a practicable guide for cases with comparably few resources. Although the reconstruction is considered a draft version, we show that it already has utility in elucidating metabolic response mechanisms to environmental toxicants by mapping gene expression data of exposure experiments to the resulting model.Author summary Genome-scale metabolic models (GEMs) are constructed based upon reconstructed networks that are carried out by an organism. The underlying biochemical knowledge in such networks can be transformed into mathematical models that could serve as a platform to answer biological questions. The availability of high-throughput biological data, including genomics, proteomics, and metabolomics data, supports the generation of such models for a large number of organisms. Nevertheless, challenges arise for non-model species which are typically less annotated. In this paper, we discuss these challenges and possible solutions in the context of generation of a draft liver reconstruction of Atlantic cod (Gadus morhua). We also show how experimental data, here gene expression data, can be mapped to the resulting model to understand the metabolic response of cod liver to environmental toxicants.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗

bioRxiv2020

The ketogenic diet is not effective in preclinical models of IDH1 wild-type and IDH1 mutant glioma

Infiltrative gliomas are the most common neoplasms arising in the brain, and remain largely incurable despite decades of research. A subset of these gliomas contains mutations in isocitrate dehydrogenase 1 (IDH1mut). This mutation disrupts cellular biochemistry, and IDH1mut gliomas are generally less aggressive than IDH1 wild-type (IDH1wt) gliomas. Some preclinical studies and clinical trials have suggested that a ketogenic diet (KD), characterized by low-carbohydrate and high-fat content, may be beneficial in slowing glioma progression. However, not all studies have shown promising results, and to date, no study has addressed whether IDH1mut gliomas might be more sensitive to KD. The aim of the current study was to compare the effects of KD in preclinical models of IDH1wt versus IDH1mut gliomas. In vitro, simulating KD by treatment with the ketone body {beta}-hydroxybutyrate had no effect on the proliferation of patient-derived IDH1wt or IDH1mut glioma cells. Likewise, KD had no effect on the in vivo growth of these patient-derived gliomas. Furthermore, mice engrafted with Sleeping-Beauty transposase-engineered IDH1wt and IDH1mut glioma showed no difference in survival while on KD. These data suggest that IDH1mut gliomas are not more responsive to KD, and that clinical trials further exploring KD in this subset of glioma patients may not be warranted.

cancer biology↗

bioRxiv2020

A parallel implementation of the Finite State Projection algorithm for the solution of the Chemical Master Equation

Stochastic reaction networks are a popular modeling framework for biochemical processes that treat the molecular copy numbers within a single cell as a continuous time Markov chain, whose forward Chapman-Kolmogorov equation is known in biochemistry literature as the chemical master equation (CME). The solution of the CME contains extremely useful information that can be compared to experimental data in order to improve the quantitative understanding of biochemical reaction networks within the cell. However, this solution is costly to compute as it requires integrating an enormous system of differential equations that grows exponentially with the number of chemical species. To address this issue, we introduce a novel multiple-sinks Finite State Projection algorithm that approximates the CME with an adaptive sequence of reduced-order models with an effecient parallelization based on MPI. The implementation is tested on models of sizable state spaces using a high-performance computing node on Amazon Web Services, showing favorable scalability.

systems biology↗

bioRxiv2020

TEARS: Spatial engineering of E. coli with addressable phase-separated RNAs

Biochemical processes often require spatial regulation and specific microenvironments. The general lack of organelles in bacteria limits the potential of bioengineering complex intracellular reactions. Here we demonstrate Transcriptionally Engineered Addressable RNA Solvent droplets (TEARS) as synthetic microdomains within the Escherichia coli. TEARS are assembled from RNA-binding protein recruitment domains fused to poly-CAG repeats that spontaneously drive liquid-liquid phase separation from the bulk cytoplasm. Targeting TEARS with fluorescent proteins revealed multilayered structures and a non-equilibrium mechanism controlling their composition and reaction robustness. We show that TEARS provide organelle-like bioprocess isolation for sequestering biochemical pathways, controlling metabolic branch points, buffering mRNA translation rates and scaffolding protein-protein interactions. TEARS are a simple and versatile tool for spatially controlling E. coli biochemistry.

synthetic biology↗