Swimming kinematics of rainbow trout behind cylinder arrays: the effect of vortex street periodicity and turbulence kinetic energy

Fish in the wild often contend with complex flows that are produced by natural and artificial structures. Research into fish interactions with turbulence often investigates metrics such as turbulence kinetic energy (TKE) or fish positional location, with less attention paid to the specific interactions between vortex organization and body swimming kinematics. Here we compare the swimming kinematics of rainbow trout ( Oncorhynchus mykiss ) holding station in flows produced by two different 3 x 5 cylinder arrays. We systematically utilized computational fluid dynamics to generate one array that produced a Kármán vortex street with high vortex periodicity and TKE (KVS array), and another that produced low periodicity and TKE, similar to a parallel vortex street (PVS array). The only difference in swimming kinematics between cylinder arrays was an increased tail beat amplitude in the KVS array. In both cylinder arrays, the tail beat frequency decreased and snout amplitude increased compared with the freestream. The center of mass amplitude was greater in the PVS array than in only the freestream, however, suggesting some buffeting of the body by the fluid. Notably, we did not observe Kármán gaiting in the KVS array as in previous studies. We hypothesize that this is because (1) vorticity was dissipated in the region where fish held station in this study and (2) cylinder arrays produced vortices that were in-line rather than staggered. These results are the first to quantify the kinematics and behavior of fishes swimming in the wake of multiple cylinder arrays, which has important implications for biomechanics, fluid dynamics, and fisheries management.

SUMMARY STATEMENT

The swimming kinematics of rainbow trout are largely preserved across two, 3 x 5 cylinder array treatments that differed in vortex periodicity and turbulence kinetic energy.

Kinematics and muscle activity of pectoral fins in rainbow trout (Oncorhynchus mykiss) station holding in turbulent flow

Pectoral fins play a crucial role in fish locomotion. Despite fishes living in complex fluid environments that exist in rivers and tidal flows, the role of the pectoral fins in navigating turbulent flows is not well understood. This study investigated the kinematics and muscle activity of pectoral fins in rainbow trout as they held station in the unsteady flows behind a D-section cylinder. We observed two distinct pectoral fin behaviors, one during braking and the other during Kármán gaiting. These behaviors were correlated to whole-body movements in response to the hydrodynamic conditions of specific regions in the cylinder wake. Sustained fin extensions during braking, where the fin was held out to maintain its position away from the body and against the flow, were associated with the cessation of forward body velocity, where the fish avoided the suction region directly downstream of the cylinder. Transient fin extensions and retractions during Kármán gaiting controlled body movements in the cross-stream direction. These two fin behaviors had different patterns of muscle activity. All braking events required recruitment from both the abductor and adductor musculature to actively extend a pectoral fin. In contrast, over 50% of fin extension movements during Kármán gaiting proceed in the absence of muscle activity. We reveal that in unsteady fluid environments, pectoral fin movements are the result of a complex combination of passive and active mechanisms that deviate substantially from canonical labriform locomotion, the implications of which await further work on the integration of sensory and motor systems.

Fantastic beasts and how to study them: rethinking experimental animal behavior

Humans have been trying to understand animal behavior at least since recorded history. Recent rapid development of new technologies has allowed us to make significant progress in understanding the physiological and molecular mechanisms underlying behavior, a key goal of neuroethology. However, there is a tradeoff when studying animal behavior and its underlying biological mechanisms: common behavior protocols in the laboratory are designed to be replicable and controlled, but they often fail to encompass the variability and breadth of natural behavior. This Commentary proposes a framework of 10 key questions that aim to guide researchers in incorporating a rich natural context into their experimental design or in choosing a new animal study system. The 10 questions cover overarching experimental considerations that can provide a template for interspecies comparisons, enable us to develop studies in new model organisms and unlock new experiments in our quest to understand behavior.

Effects of n-butanol production on metabolism and the photosystem in Synecococcus elongatus PCC 7942 based on metabolic flux and target proteome analyses

Although n-butanol (BuOH) is an ideal fuel because of its superior physical properties, it has toxicity to microbes. Previously, a Synechococcus elongatus PCC 7942 derivative strain that produces BuOH from CO2 was developed by introducing six heterologous genes (BUOH-SE strain). To identify the bottleneck in BuOH production, the effects of BuOH production and its toxicity on central metabolism and the photosystem were investigated. Parental (WT) and BUOH-SE strains were cultured under autotrophic conditions. Consistent with the results of a previous study, BuOH production was observed only in the BUOH-SE strain. Isotopically non-stationary 13C-metabolic flux analysis revealed that the CO2 fixation rate was much larger than the BuOH production rate in the BUOH-SE strain (1.70 vs 0.03 mmol gDCW-1 h-1), implying that the carbon flow for BuOH biosynthesis was less affected by the entire flux distribution. No large difference was observed in the flux of metabolism between the WT and BUOH-SE strains. Contrastingly, in the photosystem, the chlorophyll content and maximum O2 evolution rate per dry cell weight of the BUOH-SE strain were decreased to 81% and 43% of the WT strain, respectively. Target proteome analysis revealed that the amounts of some proteins related to antennae (ApcA, ApcD, ApcE, and CpcC), photosystem II (PsbB, PsbU, and Psb28-2), and cytochrome b6f complex (PetB and PetC) in photosystems decreased in the BUOH-SE strain. The activation of photosynthesis would be a novel approach for further enhancing BuOH production in S. elongatus PCC 7942.

Anion efflux mediates transduction in the hair cells of the zebrafish lateral line

Hair cells are the principal sensory receptors of the vertebrate auditory system, where they transduce sounds through mechanically gated ion channels that permit cations to flow from the surrounding endolymph into the cells. The lateral line of zebrafish has served as a key model system for understanding hair cell physiology and development, often with the belief that these hair cells employ a similar transduction mechanism. In this study, we demonstrate that these hair cells are exposed to an unregulated external environment with cation concentrations that are too low to support transduction. Our results indicate that hair cell excitation is instead mediated by a substantially different mechanism involving the outward flow of anions. Further investigation of hair cell transduction in a diversity of sensory systems and species will likely yield deep insights into the physiology of these unique cells.

An ATP-sensitive phosphoketolase regulates carbon fixation in cyanobacteria

Regulation of CO2 fixation in cyanobacteria is important both for the organism and global carbon balance. Here we show that phosphoketolase in Synechococcus elongatus PCC7942 (SeXPK) possesses a distinct ATP-sensing mechanism, where a drop in ATP level allows SeXPK to divert precursors of the RuBisCO substrate away from the Calvin-Benson-Bassham cycle. Deleting the SeXPK gene increased CO2 fixation particularly during light-dark transitions. In high-density cultures, the Δxpk strain showed a 60% increase in carbon fixation and unexpectedly resulted in sucrose secretion without any pathway engineering. Using cryo-EM analysis, we discovered that these functions were enabled by a unique allosteric regulatory site involving two subunits jointly binding two ATP, which constantly suppresses the activity of SeXPK until the ATP level drops. This magnesium-independent ATP allosteric site is present in many species across all three domains of life, where it may also play important regulatory functions.

Recording central nervous system responses of freely-swimming marine and freshwater fishes with a customizable, implantable AC differential amplifier

BACKGROUND

Fish have adapted to a diversity of environments but the neural mechanisms underlying natural aquatic behaviors are not well known.

NEW METHOD

We have developed a small, customizable AC differential amplifier and surgical procedures for recording multi-unit extracellular signals in the CNS of marine and freshwater fishes.

RESULTS

Our minimally invasive amplifier allowed fish to orient to flow and respond to hydrodynamic and visual stimuli. We recorded activity in the cerebellum during these behaviors.

COMPARISON WITH EXISTING METHODS

Our system is very low-cost, hydrodynamically streamlined, and capable of high-gain in order to allow for recordings from freely behaving, fast fishes in complex fluid environments.

CONCLUSIONS

Our tethered approach allows access to record neural activity in a diversity of adult fishes in the lab, but can also be modified for data logging in the field.

Climate change challenges, plant science solutions

Climate change is a defining challenge of the 21st century, and this decade is a critical time for action to mitigate the worst effects on human populations and ecosystems. Plant science can play an important role in developing crops with enhanced resilience to harsh conditions (e.g. heat, drought, salt stress, flooding, disease outbreaks) and engineering efficient carbon-capturing and carbon-sequestering plants. Here, we present examples of research being conducted in these areas and discuss challenges and open questions as a call to action for the plant science community.

Subtyping of major SARS-CoV-2 variants reveals different transmission dynamics based on 10 million genomes

SARS-CoV-2 continues to evolve, causing waves of the pandemic. Up to May 2022, 10 million genome sequences have accumulated, which are classified into five major variants of concern. With the growing number of sequenced genomes, analysis of the big dataset has become increasingly challenging. Here we developed systematic approaches based on sets of correlated single nucleotide variations (SNVs) for comprehensive subtyping and pattern recognition of transmission dynamics. The approach outperformed single-SNV and spike-centric scans. Moreover, the derived subtypes elucidate the relationship of signature SNVs and transmission dynamics. We found that different subtypes of the same variant, including Delta and Omicron exhibited distinct temporal trajectories. For example, some Delta and Omicron subtypes did not spread rapidly, while others did. We identified sets of characteristic SNVs that appeared to enhance transmission or decrease efficacy of antibodies for some subtypes. We also identified a set of SNVs that appeared to suppress transmission or increase viral sensitivity to antibodies. For the Omicron variant, the dominant type in the world, we identified the subtypes with enhanced and suppressed transmission in an analysis of eight million genomes as of March 2022 and further confirmed the findings in a later analysis of ten million genomes as of May 2022. While the "enhancer" SNVs exhibited an enriched presence on the spike protein, the "suppressor" SNVs are mainly elsewhere. Disruption of the SNV correlation largely destroyed the enhancer-suppressor phenomena. These results suggest the importance of fine subtyping of variants, and point to potential complex interactions among SNVs.

Evolutionary convergence of a neural mechanism in the cavefish lateral line system

Animals can evolve dramatic sensory functions in response to environmental constraints, but little is known about the neural mechanisms underlying these changes. The Mexican tetra, Astyanax mexicanus, is a leading model to study genetic, behavioral, and physiological evolution by comparing eyed surface populations and blind cave populations. We compared neurophysiological responses of posterior lateral line afferent neurons and motor neurons across A. mexicanus populations to reveal how shifts in sensory function may shape behavioral diversity. These studies indicate differences in intrinsic afferent signaling and gain control across populations. Elevated endogenous afferent activity identified a lower response threshold in the lateral line of blind cavefish relative to surface fish leading to increased evoked potentials during hair cell deflection in cavefish. We next measured the effect of inhibitory corollary discharges from hindbrain efferent neurons onto afferents during locomotion. We discovered that three independently derived cavefish populations have evolved persistent afferent activity during locomotion, suggesting for the first time that partial loss of function in the efferent system can be an evolutionary mechanism for neural adaptation of a vertebrate sensory system.

Fish-inspired segment models for undulatory steady swimming

Many aquatic animals swim by undulatory body movements and understanding the diversity of these movements could unlock the potential for designing better underwater robots. Here, we analyzed the steady swimming kinematics of a diverse group of fish species to investigate whether their undulatory movements can be represented using a series of interconnected multi-segment models, and if so, to identify the key factors driving the segment configuration of the models. Our results show that the steady swimming kinematics of fishes can be described successfully using parsimonious models, 83% of which had fewer than five segments. In these models, the anterior segments were significantly longer than the posterior segments, and there was a direct link between segment configuration and swimming kinematics, body shape, and Reynolds number. The models representing eel-like fishes with elongated bodies and fishes swimming at high Reynolds numbers had more segments and less segment length variability along the body than the models representing other fishes. These fishes recruited their anterior bodies to a greater extent, initiating the undulatory wave more anteriorly. Two shape parameters, related to axial and overall body thickness, predicted segment configuration with moderate to high success rate. We found that head morphology was a good predictor of its segment length. While there was a large variation in head segments, the length of tail segments was similar across all models. Given that fishes exhibited variable caudal fin shapes, the consistency of tail segments could be a result of an evolutionary constraint tuned for high propulsive efficiency. The bio-inspired multi-segment models presented in this study highlight the key bending points along the body and can be used to decide on the placement of actuators in fish-inspired robots, to model hydrodynamic forces in theoretical and computational studies, or for predicting muscle activation patterns during swimming.

Metabolomics-Driven Identification of the Rate-Limiting Steps in 1-Propanol Production

The concerted effort for bioproduction of higher alcohols and other commodity chemicals has yielded a consortium of metabolic engineering techniques to identify targets to enhance performance of engineered microbial strains. Here, we demonstrate the use of metabolomics as a tool to systematically identify targets for improved production phenotypes in Escherichia coli. Gas chromatography/mass spectrometry (GC/MS) and ion-pair LC-MS/MS were performed to investigate metabolic perturbations in various 1-propanol producing strains. Two initial strains were compared that differ in the expression of the citramalate and threonine pathways, which hold a synergistic relationship to maximize production yields. While this results in increased productivity, no change in titer was observed when the threonine pathway was overexpressed beyond native levels. Metabolomics revealed accumulation of upstream byproducts, norvaline and 2-aminobutyrate, both of which are derived from 2-ketobutyrate (2KB). Eliminating the competing pathway by gene knockouts or improving flux through overexpression of glycolysis gene effectively increased the intracellular 2KB pool. However, the increase in 2KB intracellular concentration yielded decreased production titers, indicating toxicity caused by 2KB and an insufficient turnover rate of 2KB to 1-propanol. Optimization of alcohol dehydrogenase YqhD activity using an ribosome binding site (RBS) library improved 1-propanol titer (g/L) and yield (g/g of glucose) by 38 and 29% in 72 h compared to the base strain, respectively. This study demonstrates the use of metabolomics as a powerful tool to aid systematic strain improvement for metabolically engineered organisms.

A cell-free self-replenishing CO2-fixing system

Biological CO2 fixation is so far the most effective means for CO2 reduction at scale and accounts for most of the CO2 fixed on Earth. Through this process, carbon is fixed in cellular components and biomass during organismal growth. To uncouple CO2 fixation from growth and cellular regulation, cell-free CO2 fixation systems represent an alternative approach since the rate can be independently manipulated. Here we designed an oxygen-insensitive, self-replenishing CO2 fixation system with opto-sensing. The system comprises a synthetic reductive glyoxylate and pyruvate synthesis (rGPS) cycle and the malyl-CoA-glycerate (MCG) pathway to produce acetyl-coenzyme A (CoA), pyruvate and malate from CO2, which are also intermediates in the cycle. We solved various problems associated with the in vitro system, and implemented opto-sensing modules to control the regeneration of cofactors. We accomplished sustained operation for 6 hours with a CO2-fixing rate comparable to or greater than typical CO2 fixation rates of photosynthetic or lithoautotrophic organisms.

The Philosophy of Outliers: Reintegrating Rare Events Into Biological Science

Individual variation in morphology, physiology, and behavior has been a topic of great interest in the biological sciences. While scientists realize the importance of understanding diversity in individual phenotypes, historically the "minority" results (i.e., outlier observations or rare events) of any given experiment have been dismissed from further analysis. We need to reframe how we view "outliers" to improve our understanding of biology. These rare events are often treated as problematic or spurious, when they can be real rare events or individuals driving evolution in a population. It is our perspective that to understand what outliers can tell us in our data, we need to: (1) Change how we think about our data philosophically, (2) Fund novel collaborations using science "weavers" in our national funding agencies, and (3) Bridge long-term field and lab studies to reveal these outliers in action. By doing so, we will improve our understanding of variation and evolution. We propose that this shift in culture towards more integrative science will incorporate diverse teams, citizen scientists and local naturalists, and change how we teach future students.

Corollary discharge enables proprioception from lateral line sensory feedback

Animals modulate sensory processing in concert with motor actions. Parallel copies of motor signals, called corollary discharge (CD), prepare the nervous system to process the mixture of externally and self-generated (reafferent) feedback that arises during locomotion. Commonly, CD in the peripheral nervous system cancels reafference to protect sensors and the central nervous system from being fatigued and overwhelmed by self-generated feedback. However, cancellation also limits the feedback that contributes to an animal's awareness of its body position and motion within the environment, the sense of proprioception. We propose that, rather than cancellation, CD to the fish lateral line organ restructures reafference to maximize proprioceptive information content. Fishes' undulatory body motions induce reafferent feedback that can encode the body's instantaneous configuration with respect to fluid flows. We combined experimental and computational analyses of swimming biomechanics and hair cell physiology to develop a neuromechanical model of how fish can track peak body curvature, a key signature of axial undulatory locomotion. Without CD, this computation would be challenged by sensory adaptation, typified by decaying sensitivity and phase distortions with respect to an input stimulus. We find that CD interacts synergistically with sensor polarization to sharpen sensitivity along sensors' preferred axes. The sharpening of sensitivity regulates spiking to a narrow interval coinciding with peak reafferent stimulation, which prevents adaptation and homogenizes the otherwise variable sensor output. Our integrative model reveals a vital role of CD for ensuring precise proprioceptive feedback during undulatory locomotion, which we term external proprioception.

Body Caudal Undulation measured by Soft Sensors and emulated by Soft Artificial Muscles

We propose the use of bio-inspired robotics equipped with soft sensor technologies to gain a better understanding of the mechanics and control of animal movement. Soft robotic systems can be used to generate new hypotheses and uncover fundamental principles underlying animal locomotion and sensory capabilities, which could subsequently be validated using living organisms. Physical models increasingly include lateral body movements, notably back and tail bending, which are necessary for horizontal plane undulation in model systems ranging from fish to amphibians and reptiles. We present a comparative study of the use of physical modeling in conjunction with soft robotics and integrated soft and hyperelastic sensors to monitor local pressures, enabling local feedback control, and discuss issues related to understanding the mechanics and control of undulatory locomotion. A parallel approach combining live animal data with biorobotic physical modeling promises to be beneficial for gaining a better understanding of systems in motion.

An Algorithmic Approach to Natural Behavior

Uncovering the mechanisms and implications of natural behavior is a goal that unites many fields of biology. Yet, the diversity, flexibility, and multi-scale nature of these behaviors often make understanding elusive. Here, we review studies of animal pursuit and evasion - two special classes of behavior where theory-driven experiments and new modeling techniques are beginning to uncover the general control principles underlying natural behavior. A key finding of these studies is that intricate sequences of pursuit and evasion behavior can often be constructed through simple, repeatable rules that link sensory input to motor output: we refer to these rules as behavioral algorithms. Identifying and mathematically characterizing these algorithms has led to important insights, including the discovery of guidance rules that attacking predators use to intercept mobile prey, and coordinated neural and biomechanical mechanisms that animals use to avoid impending collisions. Here, we argue that algorithms provide a good starting point for studies of natural behavior more generally. Rather than beginning at the neural or ecological levels of organization, we advocate starting in the middle, where the algorithms that link sensory input to behavioral output can provide a solid foundation from which to explore both the implementation and the ecological outcomes of behavior. We review insights that have been gained through such an algorithmic approach to pursuit and evasion behaviors. From these, we synthesize theoretical principles and lay out key modeling tools needed to apply an algorithmic approach to the study of other complex natural behaviors.

Identification of COVID-19 B-cell epitopes with phage-displayed peptide library

Background

Coronavirus disease 19 (COVID-19) first appeared in the city of Wuhan, in the Hubei province of China. Since its emergence, the COVID-19-causing virus, SARS-CoV-2, has been rapidly transmitted around the globe, overwhelming the medical care systems in many countries and leading to more than 3.3 million deaths. Identification of immunological epitopes on the virus would be highly useful for the development of diagnostic tools and vaccines that will be critical to limiting further spread of COVID-19.

Methods

To find disease-specific B-cell epitopes that correspond to or mimic natural epitopes, we used phage display technology to determine the targets of specific antibodies present in the sera of immune-responsive COVID-19 patients. Enzyme-linked immunosorbent assays were further applied to assess competitive antibody binding and serological detection. VaxiJen, BepiPred-2.0 and DiscoTope 2.0 were utilized for B-cell epitope prediction. PyMOL was used for protein structural analysis.

Results

36 enriched peptides were identified by biopanning with antibodies from two COVID-19 patients; the peptides 4 motifs with consensus residues corresponding to two potential B-cell epitopes on SARS-CoV-2 viral proteins. The putative epitopes and hit peptides were then synthesized for validation by competitive antibody binding and serological detection.

Conclusions

The identified B-cell epitopes on SARS-CoV-2 may aid investigations into COVID-19 pathogenesis and facilitate the development of epitope-based serological diagnostics and vaccines.

Activity of Posterior Lateral Line Afferent Neurons during Swimming in Zebrafish

Sensory systems gather cues essential for directing behavior, but animals must decipher what information is biologically relevant. Locomotion generates reafferent cues that animals must disentangle from relevant sensory cues of the surrounding environment. For example, when a fish swims, flow generated from body undulations is detected by the mechanoreceptive neuromasts, comprising hair cells, that compose the lateral line system. The hair cells then transmit fluid motion information from the sensor to the brain via the sensory afferent neurons. Concurrently, corollary discharge of the motor command is relayed to hair cells to prevent sensory overload. Accounting for the inhibitory effect of predictive motor signals during locomotion is, therefore, critical when evaluating the sensitivity of the lateral line system. We have developed an in vivo electrophysiological approach to simultaneously monitor posterior lateral line afferent neuron and ventral motor root activity in zebrafish larvae (4-7 days post fertilization) that can last for several hours. Extracellular recordings of afferent neurons are achieved using the loose patch clamp technique, which can detect activity from single or multiple neurons. Ventral root recordings are performed through the skin with glass electrodes to detect motor neuron activity. Our experimental protocol provides the potential to monitor endogenous or evoked changes in sensory input across motor behaviors in an intact, behaving vertebrate.

A numerical study of fish adaption behaviors in complex environments with a deep reinforcement learning and immersed boundary-lattice Boltzmann method

Fish adaption behaviors in complex environments are of great importance in improving the performance of underwater vehicles. This work presents a numerical study of the adaption behaviors of self-propelled fish in complex environments by developing a numerical framework of deep learning and immersed boundary-lattice Boltzmann method (IB-LBM). In this framework, the fish swimming in a viscous incompressible flow is simulated with an IB-LBM which is validated by conducting two benchmark problems including a uniform flow over a stationary cylinder and a self-propelled anguilliform swimming in a quiescent flow. Furthermore, a deep recurrent Q-network (DRQN) is incorporated with the IB-LBM to train the fish model to adapt its motion to optimally achieve a specific task, such as prey capture, rheotaxis and Kármán gaiting. Compared to existing learning models for fish, this work incorporates the fish position, velocity and acceleration into the state space in the DRQN; and it considers the amplitude and frequency action spaces as well as the historical effects. This framework makes use of the high computational efficiency of the IB-LBM which is of crucial importance for the effective coupling with learning algorithms. Applications of the proposed numerical framework in point-to-point swimming in quiescent flow and position holding both in a uniform stream and a Kármán vortex street demonstrate the strategies used to adapt to different situations.

Role of cyanobacterial phosphoketolase in energy regulation and glucose secretion under dark anaerobic and osmotic stress conditions

Primary metabolism in cyanobacteria is built on the Calvin-Benson-Bassham (CBB) cycle, oxidative pentose phosphate (OPP) pathway, Embden-Meyerhof-Parnas (EMP) pathway, and the tricarboxylic acid (TCA) cycle. Phosphoketolase (Xpk), commonly found in cyanobacteria, is an enzyme that is linked to all these pathways. However, little is known about its physiological role. Here, we show that most of the cyanobacterial Xpk surveyed are inhibited by ATP, and both copies of Xpk in nitrogen-fixing Cyanothece ATCC51142 are further activated by ADP, suggesting their role in energy regulation. Moreover, Xpk in Synechococcus elongatus PCC7942 and Cyanothece ATCC51142 show that their expressions are dusk-peaked, suggesting their roles in dark conditions. Finally, we find that Xpk in S. elongatus PCC7942 is responsible for survival using ATP produced from the glycogen-to-acetate pathway under dark, anaerobic condition. Interestingly, under this condition, xpk deletion causes glucose secretion in response to osmotic shock such as NaHCO₃, KHCO₃ and NaCl as part of incomplete glycogen degradation. These findings unveiled the role of this widespread enzyme and open the possibility for enhanced glucose secretion from cyanobacteria.

Analysis of genomic distributions of SARS-CoV-2 reveals a dominant strain type with strong allelic associations

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of COVID 19, continues to evolve since its first emergence in December 2019. Using the complete sequences of 1,932 SARS-CoV-2 genomes, various clustering analyses consistently identified six types of the strains. Independent of the dendrogram construction, 13 signature variations in the form of single nucleotide variations (SNVs) in protein coding regions and one SNV in the 5' untranslated region (UTR) were identified and provided a direct interpretation for the six types (types I to VI). The six types of the strains and their underlying signature SNVs were validated in two subsequent analyses of 6,228 and 38,248 SARS-CoV-2 genomes which became available later. To date, type VI, characterized by the four signature SNVs C241T (5'UTR), C3037T (nsp3 F924F), C14408T (nsp12 P4715L), and A23403G (Spike D614G), with strong allelic associations, has become the dominant type. Since C241T is in the 5' UTR with uncertain significance and the characteristics can be captured by the other three strongly associated SNVs, we focus on the other three. The increasing frequency of the type VI haplotype 3037T-14408T-23403G in the majority of the submitted samples in various countries suggests a possible fitness gain conferred by the type VI signature SNVs. The fact that strains missing one or two of these signature SNVs fail to persist implies possible interactions among these SNVs. Later SNVs such as G28881A, G28882A, and G28883C have emerged with strong allelic associations, forming new subtypes. This study suggests that SNVs may become an important consideration in SARS-CoV-2 classification and surveillance.

Converting Escherichia coli to a Synthetic Methylotroph Growing Solely on Methanol

Methanol, being electron rich and derivable from methane or CO₂, is a potentially renewable one-carbon (C1) feedstock for microorganisms. Although the ribulose monophosphate (RuMP) cycle used by methylotrophs to assimilate methanol differs from the typical sugar metabolism by only three enzymes, turning a non-methylotrophic organism to a synthetic methylotroph that grows to a high cell density has been challenging. Here we reprogrammed E. coli using metabolic robustness criteria followed by laboratory evolution to establish a strain that can efficiently utilize methanol as the sole carbon source. This synthetic methylotroph alleviated a so far uncharacterized hurdle, DNA-protein crosslinking (DPC), by insertion sequence (IS)-mediated copy number variations (CNVs) and balanced the metabolic flux by mutations. Being capable of growing at a rate comparable with natural methylotrophs in a wide range of methanol concentrations, this synthetic methylotrophic strain illustrates genome editing and evolution for microbial tropism changes and expands the scope of biological C1 conversion.

Oxygen consumption of drift-feeding rainbow trout: the energetic tradeoff between locomotion and feeding in flow

To forage in fast, turbulent flow environments where prey is abundant, fishes must deal with the high associated costs of locomotion. Prevailing theory suggests that many species exploit hydrodynamic refuges to minimize the cost of locomotion while foraging. Here, we challenge this theory based on direct oxygen consumption measurements of drift-feeding trout (Oncorhynchus mykiss) foraging in the freestream and from behind a flow refuge at velocities up to 100 cm s^-1 We demonstrate that refuging is not energetically beneficial when foraging in fast flows because of a high attack cost and low prey capture success associated with leaving a station-holding refuge to intercept prey. By integrating optimum foraging theory with empirical data from respirometry and video tracking, we developed a mathematical model to predict when drift-feeding fishes should exploit or avoid refuges based on prey density, size and flow velocity. Our optimum foraging and refuging model provides new mechanistic insights into locomotor costs, habitat use and prey choice of fish foraging in current-swept habitats.

Efferent modulation of spontaneous lateral line activity during and after zebrafish motor commands

Accurate sensory processing during movement requires the animal to distinguish between external (exafferent) and self-generated (reafferent) stimuli to maintain sensitivity to biologically relevant cues. The lateral line system in fishes is a mechanosensory organ that experiences reafferent sensory feedback, via detection of fluid motion relative to the body generated during behaviors such as swimming. For the first time in larval zebrafish (Danio rerio), we employed simultaneous recordings of lateral line and motor activity to reveal the activity of afferent neurons arising from endogenous feedback from hindbrain efferent neurons during locomotion. Frequency of spontaneous spiking in posterior lateral line afferent neurons decreased during motor activity and was absent for more than half of swimming trials. Targeted photoablation of efferent neurons abolished the afferent inhibition that was correlated to swimming, indicating that inhibitory efferent neurons are necessary for modulating lateral line sensitivity during locomotion. We monitored calcium activity with Tg(elav13:GCaMP6s) fish and found synchronous activity between putative cholinergic efferent neurons and motor neurons. We examined correlates of motor activity to determine which may best predict the attenuation of afferent activity and therefore what components of the motor signal are translated through the corollary discharge. Swim duration was most strongly correlated to the change in afferent spike frequency. Attenuated spike frequency persisted past the end of the fictive swim bout, suggesting that corollary discharge also affects the glide phase of burst and glide locomotion. The duration of the glide in which spike frequency was attenuated increased with swim duration but decreased with motor frequency. Our results detail a neuromodulatory mechanism in larval zebrafish that adaptively filters self-generated flow stimuli during both the active and passive phases of locomotion.NEW & NOTEWORTHY For the first time in vivo, we quantify the endogenous effect of efferent activity on afferent gain control in a vertebrate hair cell system during and after locomotion. We believe that this pervasive effect has been underestimated when afferent activity of octavolateralis systems is characterized in the current literature. We further identify a refractory period out of phase with efferent control and place this gain mechanism in the context of gliding behavior of freely moving animals.

[Effect of non-breathing-related sleep fragmentation on cognitive function in patients with cerebral small vessel disease]

Objective: To investigate the effect of non-breathing-related sleep fragmentation on cognitive function in patients with atherosclerotic cerebral small vessel disease(CSVD). Methods: Seventy-two patients with arteriosclerotic CSVD in the Department of Neurology, the Third Affiliated Hospital of Sun Yat-sen University were enrolled in this study from August 2017 to July 2018. The patients undertook MRA(Magnetic Resonance Angiography)+SWI(Susceptibility weighted imaging), polysomnography, Montreal Cognitive Inventory (MoCA) and Concise Mental State Examination (MMSE). The patients were divided into study group (≥19) and control group (<19) according to the median number of arousal events (median=19) at night. Results: The sleep efficiency, rapid eye movement (REM) sleep ratio and non-rapid eye movement-3 (NREM-3) sleep ratio of the study group were significantly lower than those of the control group (P<0.05), and the total MoCA score (18.2±4.3) , visual space score(1.9±1.4) and delayed recall score(1.4±0.9) of the study group were significantly lower than those of the control group (22.7±3.5, 2.9±1.2, 2.9±1.1, P<0.05). Conclusion: The incidence of non-breathing-related sleep fragmentation is high in CSVD patients and this kind of fragmentation is associated with cognitive impairment.

The pursuit strategy of predatory bluefish ( Pomatomus saltatrix)

A predator's ability to capture prey depends critically on how it coordinates its approach in response to a prey's motion. Flying insects, bats and raptors are capable of capturing prey with a strategy known as parallel navigation, which allows a predator to move directly towards the anticipated point of interception. It is unclear if predators using other modes of locomotion are employing this strategy when pursuing evasive prey. Using kinematic measurements and mathematical modelling, we tested whether bluefish ( Pomatomus saltatrix) pursue prey fish ( Fundulus heteroclitus) with parallel navigation. We found that the directional changes of bluefish were not consistent with this strategy, but rather were predicted by a strategy known as deviated pursuit. Although deviated pursuit requires few sensory cues and relatively modest motor coordination, a comparison of mathematical models suggested negligible differences in path length from parallel navigation, largely owing to the acceleration exhibited by bluefish near the end of a pursuit. Therefore, the strategy of bluefish is unlike flying predators, but offers comparable performance with potentially more robust control that may be well suited to the visual system and habitat of fishes. These findings offer a foundation for understanding the sensing and locomotor control of predatory fishes.

Rapid Microbiology Screening in Pharmaceutical Workflows

Recently advances in miniaturization and automation have been utilized to rapidly decrease the time to result for microbiology testing in the clinic. These advances have been made due to the limitations of conventional culture-based microbiology methods, including agar plate and microbroth dilution, which have long turnaround times and require physicians to treat patients empirically with antibiotics before test results are available. Currently, there exist similar limitations in pharmaceutical sterility and bioburden testing, where the long turnaround times associated with standard microbiology testing drive costly inefficiencies in workflows. These include the time lag associated with sterility screening within drug production lines and the warehousing cost and time delays within supply chains during product testing. Herein, we demonstrate a proof-of-concept combination of a rapid microfluidic assay and an efficient cell filtration process that enables a path toward integrating rapid tests directly into pharmaceutical microbiological screening workflows. We demonstrate separation and detection of Escherichia coli directly captured and analyzed from a mammalian (i.e., CHO) cell culture with a 3.0 h incubation. The demonstration is performed using a membrane filtration module that is compatible with sampling from bioreactors, enabling in-line sampling and process monitoring.

Behavior, Electrophysiology, and Robotics Experiments to Study Lateral Line Sensing in Fishes

The lateral line system is a sensory system unique to fishes and amphibians. It is composed of distributed mechanosensory hair cell organs on the head and body (neuromasts), which are sensitive to pressure gradients and water movements. Over the last decade, we have pursued an interdisciplinary approach by combining behavioral, electrophysiology, and robotics experiments to study this fascinating sensory system. In behavioral and electrophysiology experiments, we have studied the larval lateral line system in the model genetic organism, zebrafish (Danio rerio). We found that the lateral line system, even in 5-day-old larvae, is involved in an array of behaviors that are critical to survival, and the deflection of a single neuromast can elicit a swimming response. In robotics experiments, we used a range of physical models with distributed pressure sensors to better understand the hydrodynamic environments from the local perspective of a fish or robot. So far, our efforts have focused on extracting control-related information for a range of application scenarios including characterizing unsteady flows such as Kármán vortex streets for station holding. We also used robot models to test biological hypotheses on how morphology and movement of fishes affect lateral line sensing. Overall, with this review we aim to increase the visibility and accessibility of this multi-disciplinary research approach.

Head width influences flow sensing by the lateral line canal system in fishes

The architecture of the cephalic lateral line canal system, with distinct lines for the supraorbital, infraorbital and mandibular canals, is highly conserved among fish species. Because these canals lie on a cranial platform, the sensory input they receive is expected to change based on how flow interacts with the head and how the canal pores are spatially distributed. In this study, we explored how head width, a trait that can vary greatly between species and across ontogeny, affects flow sensing. We inserted pressure sensors into physical fish head models of varying widths (narrow, intermediate and wide) and placed these models in steady and vortical flows. We measured sensory performance in terms of detecting flow parameters (flow speed, vortex shedding frequency and cylinder diameter), sensitivity (change in pressure gradient as a function of flow speed) and signal-to-noise ratio (SNR; strength of vortex shedding frequency with respect to background). Our results show that in all model heads the amount of hydrodynamic information was maximized at the anterior region regardless of what metric we used to evaluate the sensory performance. In addition, we discovered that all model heads had the highest SNR for vortices at the intermediate flow speeds but that each head width passively optimized the SNR for different sized vortices, which may have implications for refuge and prey seeking. Our results provide insight into the sensory ecology of fishes and have implications for the design of autonomous underwater vehicles.

Directed strain evolution restructures metabolism for 1-butanol production in minimal media

Engineering a microbial strain for production sometimes entails metabolic modifications that impair essential physiological processes for growth or production. Restoring these functions may require amending a variety of non-obvious physiological networks, and thus, rational design strategies may not be practical. Here we demonstrate that growth and production may be restored by evolution that repairs impaired metabolic function. Furthermore, we use genomics, metabolomics and proteomics to identify several underlying mutations and metabolic perturbations that allow metabolism to repair. Previously, high titers of butanol production were achieved by Escherichia coli using a growth-coupled, modified Clostridial CoA-dependent pathway after all native fermentative pathways were deleted. However, production was only observed in rich media. Native metabolic function of the host was unable to support growth and production in minimal media. We use directed cell evolution to repair this phenotype and observed improved growth, titers and butanol yields. We found a mutation in pcnB which resulted in decreased plasmid copy numbers and pathway enzymes to balance resource utilization. Increased protein abundance was measured for biosynthetic pathways, glycolytic enzymes have increased activity, and adenosyl energy charge was increased. We also found mutations in the ArcAB two-component system and integration host factor (IHF) that tune redox metabolism to alter byproduct formation. These results demonstrate that directed strain evolution can enable systematic adaptations to repair metabolic function and enhance microbial production. Furthermore, these results demonstrate the versatile repair capabilities of cell metabolism and highlight important aspects of cell physiology that are required for production in minimal media.

Augmenting the Calvin-Benson-Bassham cycle by a synthetic malyl-CoA-glycerate carbon fixation pathway

The Calvin–Benson–Bassham (CBB) cycle is presumably evolved for optimal synthesis of C3 sugars, but not for the production of C2 metabolite acetyl-CoA. The carbon loss in producing acetyl-CoA from decarboxylation of C3 sugar limits the maximum carbon yield of photosynthesis. Here we design a synthetic malyl-CoA-glycerate (MCG) pathway to augment the CBB cycle for efficient acetyl-CoA synthesis. This pathway converts a C3 metabolite to two acetyl-CoA by fixation of one additional CO₂ equivalent, or assimilates glyoxylate, a photorespiration intermediate, to produce acetyl-CoA without net carbon loss. We first functionally demonstrate the design of the MCG pathway in vitro and in Escherichia coli. We then implement the pathway in a photosynthetic organism Synechococcus elongates PCC7942, and show that it increases the intracellular acetyl-CoA pool and enhances bicarbonate assimilation by roughly 2-fold. This work provides a strategy to improve carbon fixation efficiency in photosynthetic organisms.

Improving carbon fixation efficiency and reducing carbon loss have been long term goals for people working on photosynthetic organism improvement. Here, the authors design a synthetic malyl-CoA-glycerate pathway for efficient acetyl-CoA synthesis and verify its function in vitro, in E. coli and in cyanobacterium.

Rearrangement of Coenzyme A-Acylated Carbon Chain Enables Synthesis of Isobutanol via a Novel Pathway in Ralstonia eutropha

Coenzyme A (CoA)-dependent pathways have been explored extensively for the biosynthesis of fuels and chemicals. While CoA-dependent mechanisms are widely used to elongate carbon chains in a linear fashion, branch-making chemistry has not been incorporated. In this study, we demonstrated the production of isobutanol, a branched-chain alcohol that can be used as a gasoline substitute, using a novel CoA-dependent pathway in recombinant Ralstonia eutropha H16. The designed pathway is constituted of three modules: chain elongation, rearrangement, and modification. We first integrated and optimized the chain elongation and modification modules, and we achieved the production of ∼200 mg/L n-butanol from fructose or ∼30 mg/L from formate by engineered R. eutropha. Subsequently, we incorporated the rearrangement module, which features a previously uncharacterized, native isobutyryl-CoA mutase in R. eutropha. The engineered strain produced ∼30 mg/L isobutanol from fructose. The carbon skeleton rearrangement chemistry demonstrated here may be used to expand the range of the chemicals accessible with CoA-dependent pathways.

Fish Swimming in a Kármán Vortex Street: Kinematics, Sensory Biology and Energetics

Fishes often live in environments characterized by complex flows. To study the mechanisms of how fishes interact with unsteady flows, the periodic shedding of vortices behind cylinders has been employed to great effect. In particular, fishes that hold station in a vortex street (i.e., Kármán gaiting) show swimming kinematics that are distinct from their patterns of motion during freestream swimming in uniform flows, although both behaviors can be modeled as an undulatory body wave. Kármán gait kinematics are largely preserved across flow velocities. Larger fish have a shorter body wavelength and slower body wave speed than smaller fish, in contrast to freestream swimming where body wavelength and wave speed increases with size. The opportunity for Kármán gaiting only occurs under specific conditions of flow velocity and depends on the length of the fish; this is reflected in the highest probability of Kármán gaiting at intermediate flow velocities. Fish typically Kármán gait in a region of the cylinder wake where the velocity deficit is about 40% of the nominal flow. The lateral line plays a role in tuning the kinematics of the Kármán gait, since blocking it leads to aberrant kinematics. Vision allows fish to maintain a consistent position relative to the cylinder. In the dark, fish do not show the same preference to hold station behind a cylinder though Kármán gait kinematics are the same. When oxygen consumption level is measured, it reveals that Kármán gaiting represents about half of the cost of swimming in the freestream.

Refuging rainbow trout selectively exploit flows behind tandem cylinders

Fishes may exploit environmental vortices to save in the cost of locomotion. Previous work has investigated fish refuging behind a single cylinder in current, a behavior termed the Kármán gait. However, current-swept habitats often contain aggregations of physical objects, and it is unclear how the complex hydrodynamics shed from multiple structures affect refuging in fish. To begin to address this, we investigated how the flow fields produced by two D-shaped cylinders arranged in tandem affect the ability of rainbow trout (Oncorhynchus mykiss) to Kármán gait. We altered the spacing of the two cylinders from l/D of 0.7 to 2.7 (where l=downstream spacing of cylinders and D=cylinder diameter) and recorded the kinematics of trout swimming behind the cylinders with high-speed video at Re=10,000-55,000. Digital particle image velocimetry showed that increasing l/D decreased the strength of the vortex street by an average of 53% and decreased the frequency that vortices were shed by ∼20% for all speeds. Trout were able to Kármán gait behind all cylinder treatments despite these differences in the downstream wake; however, they Kármán gaited over twice as often behind closely spaced cylinders (l/D=0.7, 1.1, and 1.5). Computational fluid dynamics simulations show that when cylinders are widely spaced, the upstream cylinder generates a vortex street that interacts destructively with the downstream cylinder, producing weaker, more widely spaced and less-organized vortices that discourage Kármán gaiting. These findings are poised to help predict when fish may seek refuge in natural habitats based on the position and arrangement of stationary objects.

A non-toxic dose of cobalt chloride blocks hair cells of the zebrafish lateral line

Experiments on the flow-sensitive lateral line system of fishes have provided important insights into the function and sensory transduction of vertebrate hair cells. A common experimental approach has been to pharmacologically block lateral line hair cells and measure how behavior changes. Cobalt chloride (CoCl2) blocks the lateral line by inhibiting calcium movement through the membrane channels of hair cells, but high concentrations can be toxic, making it unclear whether changes in behavior are due to a blocked lateral line or poor health. Here, we identify a non-toxic treatment of cobalt that completely blocks lateral line hair cells. We exposed 5-day post fertilization zebrafish larvae to CoCl2 concentrations ranging from 1 to 20 mM for 15 min and measured 1) the spiking rate of the afferent neurons contacting hair cells and 2) the larvae's health and long-term survival. Our results show that a 15-min exposure to 5 mM CoCl2 abolishes both spontaneous and evoked afferent firing. This treatment does not change swimming behavior, and results in >85% survival after 5 days. Weaker treatments of CoCl2 did not eliminate afferent activity, while stronger treatments caused close to 50% mortality. Our work provides a guideline for future zebrafish investigations where physiological confirmation of a blocked lateral line system is required.

Orthogonal partial least squares/projections to latent structures regression-based metabolomics approach for identification of gene targets for improvement of 1-butanol production in Escherichia coli

Metabolomics is the comprehensive analysis of metabolites in biological systems that uses multivariate analyses such as principal component analysis (PCA) or partial least squares/projections to latent structures regression (PLSR) to understand the metabolome state and extract important information from biological systems. In this study, orthogonal PLSR (OPLSR) model-based metabolomics approach was applied to 1-butanol producing Escherichia coli to facilitate in strain improvement strategies. Here, metabolite data obtained by liquid chromatography/mass spectrometry (LC/MS) was used to construct an OPLSR model to correlate metabolite changes with 1-butanol production and rationally identify gene targets for strain improvement. Using this approach, acetyl-CoA was determined as the rate-limiting step of the pathway while free CoA was found to be insufficient for 1-butanol production. By resolving the problems addressed by the OPLSR model, higher 1-butanol productivity was achieved. In this study, the usefulness of OPLSR-based metabolomics approach for understanding the whole metabolome state and determining the most relevant metabolites was demonstrated. Moreover, it was able to provide valuable insights for selection of rational gene targets for strain improvement.

Engineering a Thermostable Keto Acid Decarboxylase Using Directed Evolution and Computationally Directed Protein Design

Keto acid decarboxylase (Kdc) is a key enzyme in producing keto acid derived higher alcohols, like isobutanol. The most active Kdc's are found in mesophiles; the only reported Kdc activity in thermophiles is 2 orders of magnitude less active. Therefore, the thermostability of mesophilic Kdc limits isobutanol production temperature. Here, we report development of a thermostable 2-ketoisovalerate decarboxylase (Kivd) with 10.5-fold increased residual activity after 1h preincubation at 60 °C. Starting with mesophilic Lactococcus lactis Kivd, a library was generated using random mutagenesis and approximately 8,000 independent variants were screened. The top single-mutation variants were recombined. To further improve thermostability, 16 designs built using Rosetta Comparative Modeling were screened and the most active was recombined to form our best variant, LLM4. Compared to wild-type Kivd, a 13 °C increase in melting temperature and over 4-fold increase in half-life at 60 °C were observed. LLM4 will be useful for keto acid derived alcohol production in lignocellulosic thermophiles.

Kinetically accessible yield (KAY) for redirection of metabolism to produce exo-metabolites

The product formation yield (product formed per unit substrate consumed) is often the most important performance indicator in metabolic engineering. Until now, the actual yield cannot be predicted, but it can be bounded by its maximum theoretical value. The maximum theoretical yield is calculated by considering the stoichiometry of the pathways and cofactor regeneration involved. Here we found that in many cases, dynamic stability becomes an issue when excessive pathway flux is drawn to a product. This constraint reduces the yield and renders the maximal theoretical yield too loose to be predictive. We propose a more realistic quantity, defined as the kinetically accessible yield (KAY) to predict the maximum accessible yield for a given flux alteration. KAY is either determined by the point of instability, beyond which steady states become unstable and disappear, or a local maximum before becoming unstable. Thus, KAY is the maximum flux that can be redirected for a given metabolic engineering strategy without losing stability. Strictly speaking, calculation of KAY requires complete kinetic information. With limited or no kinetic information, an Ensemble Modeling strategy can be used to determine a range of likely values for KAY, including an average prediction. We first apply the KAY concept with a toy model to demonstrate the principle of kinetic limitations on yield. We then used a full-scale E. coli model (193 reactions, 153 metabolites) and this approach was successful in E. coli for predicting production of isobutanol: the calculated KAY values are consistent with experimental data for three genotypes previously published.

Metabolic systems modeling for cell factories improvement

Techniques for modeling microbial bioproduction systems have evolved over many decades. Here, we survey recent literature and focus on modeling approaches for improving bioproduction. These techniques from systems biology are based on different methodologies, starting from stoichiometry only to various stoichiometry with kinetics approaches that address different issues in metabolic systems. Techniques to overcome unknown kinetic parameters using random sampling have emerged to address meaningful questions. Among those questions, pathway robustness seems to be an important issue for metabolic engineering. We also discuss the increasing significance of databases in biology and their potential impact for biotechnology.

Synaptic Ribbons Require Ribeye for Electron Density, Proper Synaptic Localization, and Recruitment of Calcium Channels

Synaptic ribbons are structures made largely of the protein Ribeye that hold synaptic vesicles near release sites in non-spiking cells in some sensory systems. Here, we introduce frameshift mutations in the two zebrafish genes encoding for Ribeye and thus remove Ribeye protein from neuromast hair cells. Despite Ribeye depletion, vesicles collect around ribbon-like structures that lack electron density, which we term "ghost ribbons." Ghost ribbons are smaller in size but possess a similar number of smaller vesicles and are poorly localized to synapses and calcium channels. These hair cells exhibit enhanced exocytosis, as measured by capacitance, and recordings from afferent neurons post-synaptic to hair cells show no significant difference in spike rates. Our results suggest that Ribeye makes up most of the synaptic ribbon density in neuromast hair cells and is necessary for proper localization of calcium channels and synaptic ribbons.

Characterization and evolution of an activator-independent methanol dehydrogenase from Cupriavidus necator N-1

Methanol utilization by methylotrophic or non-methylotrophic organisms is the first step toward methanol bioconversion to higher carbon-chain chemicals. Methanol oxidation using NAD-dependent methanol dehydrogenase (Mdh) is of particular interest because it uses NAD(+) as the electron carrier. To our knowledge, only a limited number of NAD-dependent Mdhs have been reported. The most studied is the Bacillus methanolicus Mdh, which exhibits low enzyme specificity to methanol and is dependent on an endogenous activator protein (ACT). In this work, we characterized and engineered a group III NAD-dependent alcohol dehydrogenase (Mdh2) from Cupriavidus necator N-1 (previously designated as Ralstonia eutropha). This enzyme is the first NAD-dependent Mdh characterized from a Gram-negative, mesophilic, non-methylotrophic organism with a significant activity towards methanol. Interestingly, unlike previously reported Mdhs, Mdh2 does not require activation by known activators such as B. methanolicus ACT and Escherichia coli Nudix hydrolase NudF, or putative native C. necator activators in the Nudix family under mesophilic conditions. This enzyme exhibited higher or comparable activity and affinity toward methanol relative to the B. methanolicus Mdh with or without ACT in a wide range of temperatures. Furthermore, using directed molecular evolution, we engineered a variant (CT4-1) of Mdh2 that showed a 6-fold higher K cat/K m for methanol and 10-fold lower K cat/K m for n-butanol. Thus, CT4-1 represents an NAD-dependent Mdh with much improved catalytic efficiency and specificity toward methanol compared with the existing NAD-dependent Mdhs with or without ACT activation.

An entropy-like index of bifurcational robustness for metabolic systems

Natural and synthetic metabolic pathways need to retain stability when faced against random changes in gene expression levels and kinetic parameters. In the presence of large parameter changes, a robust system should specifically avoid moving to an unstable region, an event that would dramatically change system behavior. Here we present an entropy-like index, denoted as S, for quantifying the bifurcational robustness of metabolic systems against loss of stability. We show that S enables the optimization of a metabolic model with respect to both bifurcational robustness and experimental data. We then demonstrate how the coupling of ensemble modeling and S enables us to discriminate alternative designs of a synthetic pathway according to bifurcational robustness. Finally, we show that S enables the identification of a key enzyme contributing to the bifurcational robustness of yeast glycolysis. The different applications of S demonstrated illustrate the versatile role it can play in constructing better metabolic models and designing functional non-native pathways.

Stability of Ensemble Models Predicts Productivity of Enzymatic Systems

Stability in a metabolic system may not be obtained if incorrect amounts of enzymes are used. Without stability, some metabolites may accumulate or deplete leading to the irreversible loss of the desired operating point. Even if initial enzyme amounts achieve a stable steady state, changes in enzyme amount due to stochastic variations or environmental changes may move the system to the unstable region and lose the steady-state or quasi-steady-state flux. This situation is distinct from the phenomenon characterized by typical sensitivity analysis, which focuses on the smooth change before loss of stability. Here we show that metabolic networks differ significantly in their intrinsic ability to attain stability due to the network structure and kinetic forms, and that after achieving stability, some enzymes are prone to cause instability upon changes in enzyme amounts. We use Ensemble Modelling for Robustness Analysis (EMRA) to analyze stability in four cell-free enzymatic systems when enzyme amounts are changed. Loss of stability in continuous systems can lead to lower production even when the system is tested experimentally in batch experiments. The predictions of instability by EMRA are supported by the lower productivity in batch experimental tests. The EMRA method incorporates properties of network structure, including stoichiometry and kinetic form, but does not require specific parameter values of the enzymes.