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bioRxiv2017

Spatially organizing biochemistry: choosing a strategy to translate synthetic biology to the factory

Natural biochemical systems are ubiquitously organized both in space and time. Engineering the spatial organization of biochemistry has emerged as a key theme of synthetic biology, with numerous technologies promising improved biosynthetic pathway performance. One strategy, however, may produce disparate results for different biosynthetic pathways. We propose a spatially resolved kinetic model to explore this fundamental design choice in systems and synthetic biology. We predict that two example biosynthetic pathways have distinct optimal organization strategies that vary based on pathway-dependent and cell-extrinsic factors. Moreover, we outline this design space in general as a function of kinetic and biophysical properties, as well as culture conditions. Our results suggest that organizing biosynthesis has the potential to substantially improve performance, but that choosing the appropriate strategy is key. The flexible mathematical framework we propose can be adapted to diverse biosynthetic pathways, and lays a foundation to rationally choose organization strategies for biosynthesis.

synthetic biology↗

bioRxiv2024

Effect of dataset partitioning strategies for evaluating out-of-distribution generalisation for predictive models in biochemistry

AO_SCPLOWBSTRACTC_SCPLOWQuantifying model generalization to out-of-distribution data has been a longstanding challenge in machine learning. Addressing this issue is crucial for leveraging machine learning in scientific discovery, where models must generalize to new molecules or materials. Current methods typically split data into train and test sets using various criteria -- temporal, sequence identity, scaffold, or random cross-validation -- before evaluating model performance. However, with so many splitting criteria available, existing approaches offer limited guidance on selecting the most appropriate one, and they do not provide mechanisms for incorporating prior knowledge about the target deployment distribution(s). To tackle this problem, we have developed a novel metric, AU-GOOD, which quantifies expected model performance under conditions of increasing dissimilarity between train and test sets, while also accounting for prior knowledge about the target deployment distribution(s), when available. This metric is broadly applicable to biochemical entities, including proteins, small molecules, nucleic acids, or cells; as long as a relevant similarity function is defined for them. Recognizing the wide range of similarity functions used in biochemistry, we propose criteria to guide the selection of the most appropriate metric for partitioning. We also introduce a new partitioning algorithm that generates more challenging test sets, and we propose statistical methods for comparing models based on AU-GOOD. Finally, we demonstrate the insights that can be gained from this framework by applying it to two different use cases: developing predictors for pharmaceutical properties of small molecules, and using protein language models as embeddings to build biophysical property predictors.

bioinformatics↗

bioRxiv2024

Combinatorial effector targeting (COMET) for transcriptional modulation and locus-specific biochemistry

Understanding how human gene expression is coordinately regulated by functional units of proteins across the genome remains a major biological goal. Here, we present COMET, a high-throughput screening platform for combinatorial effector targeting for the identification of transcriptional modulators. We generate libraries of combinatorial dCas9-based fusion proteins, containing two to six effector domains, allowing us to systematically investigate more than 110,000 combinations of effector proteins at endogenous human loci for their influence on transcription. Importantly, we keep full proteins or domains intact, maintaining catalytic cores and surfaces for protein-protein interactions. We observe more than 5800 significant hits that modulate transcription, we demonstrate cell type specific transcriptional modulation, and we further investigate epistatic relationships between our effector combinations. We validate unexpected combinations as synergistic or buffering, emphasizing COMET as both a method for transcriptional effector discovery, and as a functional genomics tool for identifying novel domain interactions and directing locus-specific biochemistry.

synthetic biology↗

bioRxiv2024

BC-Design: A Biochemistry-Aware Framework for High-Precision Inverse Protein Folding

Inverse protein design (IPD) extends the classical problem of inverse protein folding (IPF) by not only recovering a sequence compatible with a given backbone geometry but also generating a range of new sequences that satisfy the physicochemical constraints required for a stable fold with a specified (often designed) function. Recent progress has incorporated biochemical properties as discrete per-residue features, but such localized signals cannot represent the continuous hydrophobic and electrostatic environments that span protein surfaces and interior volumes. Here we introduce BC-DO_SCPLOWESIGNC_SCPLOW, a biochemistry-aware inverse design framework that integrates geometric structure with smoothly varying hydrophobicity and charge properties. The later are represented independent of residue coordinates, on compact point clouds sampled throughout protein surfaces and interiors. This formulation provides a natural spatial description of physicochemical environments and enriches structural cues without specifying amino-acid identities. On the CATH 4.2 benchmark, BC-DO_SCPLOWESIGNC_SCPLOW achieves 90% sequence recovery and generalizes robustly across protein lengths, contact-order regimes, and major fold classes. Masking experiments further demonstrate an interpretable fidelity-diversity control: full biochemical context yields high-fidelity reconstructions, whereas withholding information enables exploratory variant generation. Beyond diagnostic benchmarks, BC-DO_SCPLOWESIGNC_SCPLOW demonstrably improves functional design outcomes across diverse settings. It increases enzyme-substrate affinity, enhances peptide-receptor design accuracy, and achieves state-of-the-art recovery and structural fidelity in antibody loop (CDRH3) modeling. In these applications, the model not only reconstructs native-like sequences but also proposes plausible functional variants that preserve catalytic or binding geometry--such as generating CDRH3 loops that maintain antigen-contact configurations while offering new sequence solutions. These results show that integrating continuous physicochemical properties with structural geometry enables practical, function-oriented protein design, going beyond backbone-conditioned recovery.

bioinformatics↗

bioRxiv2025

Vascular Biomechanics and Brain Biochemistry in Aged and Alzheimer's Disease Mouse Models

Age-related vascular changes accompany or precede the development of Alzheimers disease (AD) pathology. The comorbidity of AD and arterial stiffening may suggest that vascular changes have a pathogenic role. Carotid artery mechanics and hemodynamics have been associated with age-related cognitive decline. However, the impact of hemodynamics and vascular mechanics on regional vulnerability within the brain have not been thoroughly explored. Despite the venous systems role in transport, the impact of age-related alterations of the brain venous circulation on cognitive impairment is much less understood compared to the arterial system. By studying vascular mechanics and the resulting spatially-resolved brain lipids in young and aged AD mice, we can determine the relationship between vascular stiffening and brain function. Young and aged female 3xTg mice and age-matched controls were imaged using a combination of ultrasound and mass spectrometry. Wall shear stress varied across age and AD (p<0.05). The circumferential cyclic strain values for the carotid arteries and the WSS values for the jugular veins between groups were measured but were not statistically significant. Both mean velocity and pulsatility index (PI) varied across age and AD (p<0.05). Liquid chromatography mass spectrometry (LC-MS) of brain tissue identified several lipids and metabolites with statistically significant quantities (p<0.05). The fold change was computed for young AD vs. young control, aged AD vs. aged control, aged control vs. young control, and aged AD vs. young AD. The abundance of several lipid headgroups changed significantly with respect to age and AD. Phosphatidylcholines (PC), phosphatidylethanolamines (PE), cardiolipins (CL), phosphatidylserines (PS), and lysophosphatidylcholines (LPC) have been shown to decrease with AD in previous studies. However, we observed a statistically significant increase in PC, PE, CL, PS, and LPC in the aged 3xTG mouse model compared to aged controls. Hexosylceramides (HexCer), ceramides (CER) and sphingomyelin (SM), classes of sphingolipids; lysophosphatidylethanolamine (LPE), a class of phospholipids; and onogalactosyl diglycerides (MGDG), a class of glycerolipids, have been shown to increase with AD in previous studies which aligns with the statistically significant increase of LPC, HexCer, CER, SM, LPE, and MDG observed in the aged 3xTg group compared to controls in this work. Combining both ultrasound imaging and mass spectrometry, we were able determine significant differences in the vascular biomechanics and brain biochemistry seen with aging and AD.

neuroscience↗

bioRxiv2025

IDENTIFYING MISCONCEPTIONS ABOUT PROTEIN STRUCTURE AND FUNCTION IN A NON-MAJORS BIOCHEMISTRY COURSE

Understanding the structure and function of proteins is crucial for students as it provides fundamental insights into one of the central building blocks of life. Yet, undergraduate students struggle to make sense of proteins and apply knowledge about why structure affects function. Here, we expand on an existing typology of common protein misconceptions (Robic, 2010). We recruited participants from a large, lecture-based non-major biochemistry course to participate in a series of assessments that allowed us to qualitatively examine their responses. We found that the common misconceptions included: protein stability based on orientation, confusions about the inherent dynamic properties of proteins, and protein structure related to function. We surmise that all three of these newly reported, nuanced misconceptions are the product of difficulties with visuospatial reasoning.

scientific communication and education↗

bioRxiv2025

Metadimensional simulation for biochemistry and pharmacology learning

The integration of active learning strategies in health education is essential for improving student engagement and understanding, particularly in basic sciences like pharmacology and biochemistry. However, these disciplines are often perceived as abstract and disconnected from clinical practice. The aim was to develop and evaluate two innovative, live-action simulations for teaching fundamental concepts in pharmacokinetics and enzyme kinetics, using accessible materials and student-centered design. The study involved 305 students from health-related undergraduate and graduate programs. Two simulations were designed: a pharmacokinetics (PK) simulation representing systemic circulation and drug metabolism using plastic blocks and classroom stations; an enzyme kinetics (EK) simulation using both digital slides and physical block sets to model substrate-product reactions and construct Michaelis-Menten curves. Student perceptions were measured using a Likert-scale instrument adapted from validated educational models. Quantitative data (pharmacokinetic and enzymatic curves) were also generated from simulation outcomes. Students successfully built representative pharmacokinetic and enzymatic activity curves, allowing exploration of key concepts such as drug absorption, metabolism, Cmax, Tmax, half-life, and enzyme-substrate reaction rates. Perception surveys revealed high approval levels, particularly regarding the effectiveness, engagement, and collaborative aspects of the simulations. Over 85% of participants preferred the simulation-based approach over traditional lectures. These live-action activities represent a novel, effective, and low-cost strategy for enhancing the teaching of basic sciences in health education. The methods promote experiential learning, integrate cognitive, affective, and psychomotor domains, and foster student autonomy and motivation. These findings support the broader application of active methodologies in foundational science curricula.

pharmacology and toxicology↗

bioRxiv2018

The thermodynamic landscape of carbon redox biochemistry

Redox biochemistry plays a key role in the transduction of chemical energy in living systems. However, the compounds observed in metabolic redox reactions are a minuscule fraction of chemical space. It is not clear whether compounds that ended up being selected as metabolites display specific properties that distinguish them from non-biological compounds. Here we introduce a systematic approach for comparing the chemical space of all possible redox states of linear-chain carbon molecules to the corresponding metabolites that appear in biology. Using cheminformatics and quantum chemistry, we analyze the physicochemical and thermodynamic properties of the biological and non-biological compounds. We find that, among all compounds, aldose sugars have the highest possible number of redox connections to other molecules. Metabolites are enriched in carboxylic acid functional groups and depleted of carbonyls, and have higher solubility than non-biological compounds. Upon constructing the energy landscape for the full chemical space as a function of pH and electron donor potential, we find that over a large range of conditions metabolites tend to have lower Gibbs energies than non-biological molecules. Finally, we generate Pourbaix phase diagrams that serve as a thermodynamic atlas to indicate which compounds are local and global energy minima in redox chemical space across a set of pH values and electron donor potentials. Our work yields insight into the physicochemical principles governing redox metabolism, and suggests that thermodynamic stability in aqueous environments may have played an important role in early metabolic processes.

systems biology↗

bioRxiv2026

Amplicon/Protein Bead Display enables quantitative in vitro biochemistry at scale

Scalable methods for producing and characterizing protein libraries are essential for generating standardized datasets needed to train models linking sequence to function. Here, we present Amplicon/Protein Bead Display (APB-Display), which expresses and purifies >100,000 protein variants in vitro in 1 day. APB-Display uses particle-templated emulsification to generate libraries of hydrogel beads that covalently display many copies of a given protein variant and its encoding DNA. By incubating beads with fluorescently-labeled ligands, sorting, and sequencing to generate titration curves (APB-TiteSeq), we simultaneously quantified expression levels and binding affinities (Kds) for >18,000 FLAG epitope variants interacting with M2 anti-FLAG antibody in 3 days, revealing chemistry-dependent epistasis between positions 4 and 5. Single-concentration binding measurements (APB-SortSeq) paired with neural network denoising further returned quantitative affinities for >88,000 variants. APB-Display requires only standard laboratory equipment and access to a FACS sorter, providing an accessible platform for quantitative in vitro biochemistry at scale.

biophysics↗

bioRxiv2026

Slow stress-load accumulation dominates BDNF-dependent gain in a ten-state computational model of stress biochemistry

BackgroundAcute stress responses are often reversible, whereas sustained stress can produce coordinated disruption across endocrine, metabolic, inflammatory, antioxidant, and neuroplastic pathways. The Tiered Stress Biochemistry Model (TSBM) is a hypothesis-generating ten-state ordinary differential-equation framework linking a stylized cortisol signal to noradrenergic drive, vitamin C, a phenomenological aldosterone/renin-angiotensin drive, magnesium, normalized BDNF-related and Nrf2-related states, inflammation, and tryptophan-kynurenine metabolism. MethodsFive prespecified scenarios (normal, acute, chronic, depression-like, and low-cortisol PTSD-like) were simulated for 168 hours. Analyses included local stability, output-specific sensitivity screening, structural ablation, a 400-draw Latin-hypercube scan over independent {+/-} 20% parameter ranges, uncertainty distributions for threshold-crossing times, a success-conditioned parameter-trade-off screen, and a wider scan in which hypothesized BDNF-feedback gain magnitudes varied log-uniformly from 0.1 to 10 times nominal. Parameters were classified as literature-derived, literature-constrained/model-defined, calibrated, or hypothesized. ResultsUnder the specified forcing assumptions, sustained stress produced coordinated changes across several pathways. In the depression-like scenario, removing slow stress-load accumulation increased day-7 BDNF-related activity from 47.2% to 82.6%, reduced inflammation from 14.63 to 2.15 arbitrary units, and lowered KYN/TRP from 0.173 to 0.057. Removing BDNF-dependent gain increased BDNF only to 49.1% and delayed KYN/TRP crossing by 2.5 hours. The stricter multi-output conclusion was retained in 91% of uncertainty draws. Median crossing times retained the nominal sequence, but the complete four-event order occurred in only 43% of all draws. ConclusionsWithin this reduced model, a shared slow stress-load process coordinates the high-exposure state, whereas BDNF-dependent feedback acts mainly as an amplifier. The model generates an experimentally testable staging hypothesis: under sustained high-exposure forcing, magnesium changes may precede later BDNF-related and KYN/TRP changes. Longitudinal studies are required to determine whether this sequence occurs biologically, whether it is reversible, and whether it has clinical relevance. The simulations are not diagnostic or treatment recommendations.

systems biology↗

bioRxiv2020

Visual Biochemistry: modular microfluidics enables kinetic insight from time-resolved cryo-EM

Mechanistic understanding of biochemical reactions requires structural and kinetic characterization of the underlying chemical processes. However, no single experimental technique can provide this information in a broadly applicable manner and thus structural studies of static macromolecules are often complemented by biophysical analysis. Moreover, the common strategy of utilizing mutants or crosslinking probes to stabilize otherwise short-lived reaction intermediates is prone to trapping off-pathway artefacts and precludes determining the order of molecular events. To overcome these limitations and allow visualisation of biochemical processes at near-atomic spatial resolution and millisecond time scales, we developed a time-resolved sample preparation method for cryo-electron microscopy (trEM). We integrated a modular microfluidic device, featuring a 3D-mixing unit and a delay line of variable length, with a gas-assisted nozzle and motorised plunge-freeze set-up that enables automated, fast, and blot-free sample vitrification. This sample preparation not only preserves high-resolution structural detail but also substantially improves protein distribution across the vitreous ice. We validated the method by examining the formation of RecA filaments on single-stranded DNA. We could reliably visualise reaction intermediates of early filament growth across three orders of magnitude on sub-second timescales. Quantification of the trEM data allowed us to characterize the kinetics of RecA filament growth. The trEM method reported here is versatile, easy to reproduce and thus readily adaptable to a broad spectrum of fundamental questions in biology.

biochemistry↗

bioRxiv2020

Changes in biochemistry and histochemical characteristics during somatic embryogenesis in Ormosia henryi Prain

Mature embryos were used as an explant for embryogenic callus (EC) induction, and then EC was further developed to form somatic embryos during somatic embryogenesis (SE) of Ormosia henryi Prain; however, some mature embryos could induced non-embryogenic callus (NEC), browning callus (BC) or snowflake callus (SC). These phenomena might be related to the biochemical and histochemical differences during somatic embryo induction. The present study was conducted to analyze the biochemical events and histochemical changes at different SE stages in 0. henryi. The contents of soluble sugar, starch, soluble protein, H2O2, and endogenous hormones and the activities of polyphenoloxidase (PPO), superoxide dismutase (SOD), ascorbate peroxidase (APX), peroxidase (POD) and catalase (CAT) were measured at different SE stages, such as EC, globular embryo (GE), and cotyledon embryo (CE), and in abnormal tissue, such as NEC, BC, and SC. The results showed that the contents of soluble sugar and starch; the activities of PPO, SOD, APX and POD; and the ratios of indole-3-acetic acid/abscisic acid (IAA/ABA), IAA/gibberellins (IAA/GAs), auxin /GAs (AUX/GAs), and AUX/ABA decreased gradually at different SE stages. In contrast, the contents of soluble protein, H2O2, all endogenous hormones gradually increased. However, CAT activity and the ratios of IAA/cytokinins (IAA/CKs), AUX/CKs, ABA/CKs, and GAs/CKs first increased and then decreased. The high contents of GAs and ABA, high ratios of ABA/CKs and GAs/CKs and low ratios of IAA/ABA, IAA/GAs, AUX/GAs and AUX/ABA were responsible for the inability of the callus to form EC. The low enzyme activities, low contents of energy substances and H2O2 were related to NEC formation. The high contents of soluble sugar, H2O2, AUX, CKs and PPO activity and the low content of soluble protein were the basic causes of BC formation. The high-energy substances contents and low activities of SOD and POD facilitated SC formation. Histochemical observation showed that starch granule staining gradually lightened with SE development, but protein granules were darkly stained. Compared with EC, starch and protein granules were stained darker in SC, and lighter in NEC and BC. These results showed that energy substances were the material basis of SE, which affected enzyme activities, regulated reactive oxygen species (ROS) metabolism, and thus regulated the morphogenesis and development of somatic embryos. In addition, the contents and ratios of endogenous hormones affected the dedifferentiation, dedifferentiation and embryogenesis of somatic cells. To induce EC from mature embryos and further develop their formation into somatic embryos, it is necessary to adjust the energy supply and hormone ratio in the medium. One-sentence summarySomatic embryogenesis and abnormal callus tissues formation of Ormosia henryi Prain were associated with energy substances, reactive oxygen species, enzyme activities and endogenous hormones, as well as histochemical characteristics.

biochemistry↗

bioRxiv2020

Comparative biochemistry of four polyester (PET) hydrolases

The potential of bioprocessing in a circular plastic economy has strongly stimulated research in enzymatic degradation of different synthetic resins. Particular interest has been devoted to the commonly used polyester, poly(ethylene terephthalate) (PET), and a number of PET hydrolases have been described. However, a kinetic framework for comparisons of PET hydrolases (or other plastic degrading enzymes) acting on the insoluble substrate, has not been established. Here, we propose such a framework and test it against kinetic measurements on four PET hydrolases. The analysis provided values of kcat and KM, as well as an apparent specificity constant in the conventional units of M-1s-1. These parameters, together with experimental values for the number of enzyme attack sites on the PET surface, enabled comparative analyses. We found that the PET hydrolase from Ideonella sakaiensis was the most efficient enzyme at ambient conditions, and that this relied on a high kcat rather than a low KM. Moreover, both soluble and insoluble PET fragments were consistently hydrolyzed much faster than intact PET. This suggests that interactions between polymer strands slow down PET degradation, while the chemical steps of catalysis and the low accessibility associated with solid substrate were less important for the overall rate. Finally, the investigated enzymes showed a remarkable substrate affinity, and reached half the saturation rate on PET, when the concentration of attack sites in the suspension was only about 50 nM. We propose that this is linked to nonspecific adsorption, which promotes the nearness of enzyme and attack sites.

biochemistry↗

bioRxiv2024

Control of Molecular Biochemistry and Cell Injury Responses through Highly Ordered Supramolecular Assembly of Flavonoids

Flavonoids are phytonutrients commonly found in plant-based foods and are generally known for their health benefits. However, their utility as potential therapeutics has not been explored because their presence in drug development tests can lead to false positives due to non-specific binding. Here, we employed molecular dynamic simulations (MDS) to examine flavonoid behavior and discovered that they form highly organized supramolecular assemblies that physically interact with disordered regions of enzymatic proteins and can physically interlink multiple protein molecules. These flavonoid assemblies adopt secondary structural patterns like those found in proteins and nucleic acids, and they physically influence molecular movement and tertiary protein structure, thereby modulating the biochemical activities of a diverse range of enzymes. Moreover, in the presence of flavonoids, human cells are protected against injury caused by ultraviolet radiation. These findings unveil a novel form of biochemical regulation wherein small molecules can modulate the function of larger proteins by forming supramolecular assemblies which results in enhanced molecular and cellular resilience. Single Sentence SummaryMolecular dynamic simulations led to the discovery that flavonoid phytonutrients can self-assemble into highly ordered supramolecular structures that interact with enzymatic proteins, slow biochemical activities, and protect cells against injury.

biochemistry↗

bioRxiv2024

From Molecules to Behavior: Linking Brain Biochemistry in the Dorsal Anterior Cingulate Cortex to 'Anxiety to Eat' Responses in Anorexia Nervosa

Anorexia nervosa (AN) is a mental and behavioral health condition characterized by an intense fear of body weight or fat gain, restriction of food intake resulting in low body weight, and distorted body image. Substantial research has focused on general anxiety in AN, but less is known about eating-related anxiety and its underlying neurobiological mechanisms. We sought to characterize anxiety-to-eat in AN and to examine neurometabolite levels in the dorsal anterior cingulate cortex (dACC), a brain region putatively involved in modulating anxiety-related responses, using edited magnetic resonance spectroscopy. Sixteen women hospitalized with AN and 16 women of healthy weight without a lifetime history of an eating disorder (healthy controls; HC) completed a computer-based behavioral task assessing anxiety-to-eat in response to images of higher (HED) and lower energy density (LED) foods. The AN group reported greater anxiety to eat HED and LED foods relative to the HC group. Both groups reported greater anxiety to eat HED foods relative to LED foods. The neurometabolite myo-inositol (myo-I) was lower in the dACC in AN relative to HC. In the AN group only, myo-I levels negatively predicted anxiety to eat HED but not LED foods and was independent of body mass index, duration of illness, and general anxiety. These findings provide new insight into the clinically challenging feature of eating-related anxiety in AN, and indicate potential for myo-I levels in the dACC to serve as a novel biomarker of illness severity or therapeutic target in individuals vulnerable to AN.

biochemistry↗

bioRxiv2019

Addressing lipid structural diversity in signalling: Photochemical probes for live-cell lipid biochemistry

Every cell produces thousands of distinct lipid species, but methodology for studying the biological roles of individual lipids is insufficient. Using the example of diacylglycerols, prominent second messengers, we here investigate whether lipid chemical diversity can provide a basis for cellular signal specification. We developed novel photo-caged lipid probes, which allow acute manipulation of distinct diacylglycerol species in the plasma membrane. Combining uncaging experiments with mathematical modelling enabled the determination of binding constants for diacylglycerol-protein interactions and kinetic parameters for diacylglycerol transbilayer movement and turnover in quantitative live-cell experiments. Strikingly, we find that affinities and kinetics vary by orders of magnitude due to diacylglycerol structural diversity. These differences are sufficient to explain differential recruitment of diacylglycerol binding proteins and thus differing downstream phosphorylation patterns. Our approach represents a generally applicable method for elucidating the biological function of single lipid species on subcellular scales.

biochemistry↗

bioRxiv2026

A new player in the biochemistry of Anammox bacteria: a multidomain HAO-like protein

Anaerobic ammonium-oxidizing (anammox) bacteria are essential players in the global nitrogen cycle, responsible for converting ammonium and nitrite directly to nitrogen gas. Anammox bacteria have unique features such as a specialized cellular compartment - the anammoxosome. Candidatus (Ca.) Brocadia pituitae genome, as other anammox bacteria, encodes for a diversity of hydroxylamine oxidoreductase (HAO) paralogs, often pointed out as the enzymes responsible for most of the reactions of the anammox cycle. One of this Ca. B. pituitae HAO paralogs is an 840-amino acids protein, named here as BpMHAO, that stands out for its unprecedented domain organization, which includes a multicopper oxidase-like (MCo-like) domain followed by the HAO-like one. Sequence and structural analyses classified this MCo-like domain as homologous to the small laccase family. Spectroscopic characterization revealed a distinct UV-visible spectrum, tentatively assigned to the T3 center, whereas the EPR spectra confirmed the presence of T1, T2 and T3 copper centers. Enzymatic studies demonstrated limited laccase and oxygen-dependent ferroxidase activities. On the other hand, enzymatic assays performed in cell extracts from Escherichia coli and Shewanella oneidensis, harbouring the recombinant HAO-like domain, exhibited a robust hydroxylamine reductase activity using methyl viologen as the electron donor. Our results showed that the BpMHAO potentially plays a role in the anammox process/reactions by converting hydroxylamine into hydrazine. This feature can be relevant to anammox bacteria either by i) mitigating unwanted hydroxylamine, obtained by incorrect formation of this compound, by converting it into hydrazine and enabling its use in the anammox reaction or ii) using hydroxylamine from the outside medium as a substitute for ammonium, delivering hydrazine directly to the last step of the cycle, short-circuiting its first steps.

biochemistry↗

bioRxiv2016

Local chromosome context is a major determinant of crossover pathway biochemistry during budding yeast meiosis

Meiotic chromosomes are divided into regions of enrichment and depletion for meiotic chromosome axis proteins, in budding yeast Hop1 and Red1. These proteins are important for formation of Spo11-catalyzed DSB, but their contribution to crossover recombination is undefined. By studying meiotic recombination initiated by the sequence-specific VMA1-derived endonuclease (VDE), we show that meiotic chromosome structure helps to determine the biochemical mechanism by which recombination intermediates are resolved to form crossovers. At a Hop1-enriched locus, most VDE-initiated crossovers required the MutL{gamma} resolvase, which forms most Spo11-initiated crossovers. In contrast, at a locus with lower Hop1 occupancy, most VDE-initiated crossovers were MutL{gamma}-independent. In pch2 mutants, the two loci displayed similar Hop1 occupancy levels, and also displayed similar MutL{gamma}-dependence of VDE-induced crossovers. We suggest that meiotic and mitotic recombination pathways coexist within meiotic cells, with features of meiotic chromosome structure partitioning the genome into regions where one pathway or the other predominates.

Genetics↗