Allosteric Regulation of Glycogen Phosphorylase by Order/Disorder Transition of the 250' and 280s Loops.

Allostery is a fundamental mechanism of protein activation, yet the precise dynamic changes that underlie functional regulation of allosteric enzymes, such as glycogen phosphorylase (GlyP), remain poorly understood. Despite being the first allosteric enzyme described, its structural regulation is still a challenging problem: the key regulatory loops of the GlyP active site (250' and 280s) are weakly stable and often missing density or have large b-factors in structural models. This led to the longstanding hypothesis that GlyP regulation is achieved through gating of the active site by (dis)order transitions, as first proposed by Barford and Johnson. However, testing this requires a quantitative measurement of weakly stable local structure which, to date, has been technically challenging in such a large protein. Hydrogen-deuterium-exchange mass spectrometry (HDX-MS) is a powerful tool for studying protein dynamics, and millisecond HDX-MS has the ability to measure site-localized stability differences in weakly stable structures, making it particularly valuable for investigating allosteric regulation in GlyP. Here, we used millisecond HDX-MS to measure the local structural perturbations of glycogen phosphorylase b (GlyPb), the phosphorylated active form (GlyPa), and the inhibited glucose-6 phosphate complex (GlyPb:G6P) at near-amino acid resolution. Our results support the Barford and Johnson hypothesis for GlyP regulation by providing insight into the dynamic changes of the key regulatory loops.

Online Fully Automated System for Hydrogen/Deuterium-Exchange Mass Spectrometry with Millisecond Time Resolution.

Amide hydrogen/deuterium-exchange mass spectrometry (HDX-MS) is a powerful tool for analyzing the conformational dynamics of proteins in a solution. Current conventional methods have a measurement limit starting from several seconds and are solely reliant on the speed of manual pipetting or a liquid handling robot. Weakly protected regions of polypeptides, such as in short peptides, exposed loops and intrinsically disordered the protein exchange on the millisecond timescale. Typical HDX methods often cannot resolve the structural dynamics and stability in these cases. Numerous academic laboratories have demonstrated the considerable utility of acquiring HDX-MS data in the sub-second regimes. Here, we describe the development of a fully automated HDX-MS apparatus to resolve amide exchange on the millisecond timescale. Like conventional systems, this instrument boasts automated sample injection with software selection of labeling times, online flow mixing and quenching, while being fully integrated with a liquid chromatography-MS system for existing standard "bottom-up" workflows. HDX-MS's rapid exchange kinetics of several peptides demonstrate the repeatability, reproducibility, back-exchange, and mixing kinetics achieved with the system. Comparably, peptide coverage of 96.4% with 273 peptides was achieved, supporting the equivalence of the system to standard robotics. Additionally, time windows of 50 ms-300 s allowed full kinetic transitions to be observed for many amide groups; especially important are short time points (50-150 ms) for regions that are likely highly dynamic and solvent- exposed. We demonstrate that information on structural dynamics and stability can be measured for stretches of weakly stable polypeptides in small peptides and in local regions of a large enzyme, glycogen phosphorylase.

The changing physical and ecological meanings of North Pacific Ocean climate indices.

Climate change is likely to change the relationships between commonly used climate indices and underlying patterns of climate variability, but this complexity is rarely considered in studies using climate indices. Here, we show that the physical and ecological conditions mapping onto the Pacific Decadal Oscillation (PDO) index and North Pacific Gyre Oscillation (NPGO) index have changed over multidecadal timescales. These changes apparently began around a 1988/1989 North Pacific climate shift that was marked by abrupt northeast Pacific warming, declining temporal variance in the Aleutian Low (a leading atmospheric driver of the PDO), and increasing correlation between the PDO and NPGO patterns. Sea level pressure and surface temperature patterns associated with each climate index changed after 1988/1989, indicating that identical index values reflect different states of basin-scale climate over time. The PDO and NPGO also show time-dependent skill as indices of regional northeast Pacific ecosystem variability. Since the late 1980s, both indices have become less relevant to physical-ecological variability in regional ecosystems from the Bering Sea to the southern California Current. Users of these climate indices should be aware of nonstationary relationships with underlying climate variability within the historical record, and the potential for further nonstationarity with ongoing climate change.

Interconversion of Unexpected Thiol States Affects the Stability, Structure, and Dynamics of Antibody Engineered for Site-Specific Conjugation.

Antibody-drug conjugates have become one of the most actively developed classes of drugs in recent years. Their great potential comes from combining the strengths of large and small molecule therapeutics: the exquisite specificity of antibodies and the highly potent nature of cytotoxic compounds. More recently, the approach of engineering antibody-drug conjugate scaffolds to achieve highly controlled drug to antibody ratios has focused on substituting or inserting cysteines to facilitate site-specific conjugation. Herein, we characterize an antibody scaffold engineered with an inserted cysteine that formed an unexpected disulfide bridge during manufacture. A combination of mass spectrometry and biophysical techniques have been used to understand how the additional disulfide bridge forms, interconverts, and changes the stability and structural dynamics of the antibody intermediate. This quantitative and structurally resolved model of the local and global changes in structure and dynamics associated with the engineering and subsequent disulfide-bonded variant can assist future engineering strategies.

Long-Range Conformational Changes in Monoclonal Antibodies Revealed Using FPOP-LC-MS/MS.

Differences in conformational dynamics between two full-length monoclonal antibodies have been probed in detail using Fast Photochemical Oxidation of Proteins (FPOP) followed by proteolysis and LC-ESI-MS/MS analyses. FPOP uses hydroxyl radical labeling to probe the surface-accessible regions of proteins and has the advantage that the resulting covalent modifications are irreversible, thus permitting optimal downstream analysis. Despite the two monoclonal antibodies (mAbs) differing by only three amino acids in the heavy chain complementarity determining regions (CDRs), one mAb, MEDI1912-WFL, has been shown to undergo reversible self-association at high concentrations and exhibited poor pharmacokinetic properties in vivo, properties which are markedly improved in the variant, MEDI1912-STT. Identifying the differences in oxidative labeling between the two antibodies at residue level revealed long-range effects which provide a key insight into their conformational differences. Specifically, the amino acid mutations in the CDR region of the heavy chain resulted in significantly different labeling patterns at the interfaces of the CL-CH1 and CH1-CH2 domains, with the nonaggregating variant undergoing up to four times more labeling in this region than the aggregation prone variant, thus suggesting a change in the structure and orientation of the CL-CH1 interface. The wealth of FPOP and LC-MS data obtained enabled the study of the LC elution properties of FPOP-oxidized peptides. Some oxidized amino acids, specifically histidine and lysine, were noted to have unique effects on the retention time of the peptide, offering the promise of using such an analysis as an aid to MS/MS in assigning oxidation sites.

Subregional differences in groundfish distributional responses to anomalous ocean bottom temperatures in the northeast Pacific.

Although climate-induced shifts in fish distribution have been widely reported at the population level, studies that account for ontogenetic shifts and subregional differences when assessing responses are rare.In this study, groundfish distributional changes in depth, latitude, and longitude were assessed at different size classes by species within nine subregions. We examined large, quality-controlled datasets of depth-stratified-random bottom trawl surveys conducted during summer in three large regions-the Gulf of Alaska and the west coasts of Canada and the United States-over the period 1996-2015, a time period punctuated by a marine "heat wave." Temporal biases in bottom temperature were minimized by subdividing each region into three subregions, each with short-duration surveys. Near-bottom temperatures, weighted by stratum area, were unsynchronized across subregions and exhibited varying subregional interannual variability. The weighted mean bottom depths in the subregions also vary largely among subregions. The centroids (centers of gravity) of groundfish distribution were weighted with catch per unit effort and stratum area for 10 commercially important groundfish species by size class and subregion. Our multivariate analyses showed that there were significant differences in aggregate fish movement responses to warm temperatures across subregions but not among species or sizes. Groundfish demonstrated poleward responses to warming temperatures only in a few subregions and moved shallower or deeper to seek colder waters. The temperature responses of groundfish depended on where they were. Under global warming, groundfish may form geographically distinct thermal ecoregions along the northeast Pacific shelf. Shallow-depth species exhibited greatly different distributional responses to temperature changes across subregions while deep-depth species of different subregions tend to have relatively similar temperature responses. Future climate studies would benefit by considering fish distributions on small subregional scales.

Lipid zonation and phospholipid remodeling in nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease (NAFLD) can progress from simple steatosis (i.e., nonalcoholic fatty liver [NAFL]) to nonalcoholic steatohepatitis (NASH), cirrhosis, and cancer. Currently, the driver for this progression is not fully understood; in particular, it is not known how NAFLD and its early progression affects the distribution of lipids in the liver, producing lipotoxicity and inflammation. In this study, we used dietary and genetic mouse models of NAFL and NASH and translated the results to humans by correlating the spatial distribution of lipids in liver tissue with disease progression using advanced mass spectrometry imaging technology. We identified several lipids with distinct zonal distributions in control and NAFL samples and observed partial to complete loss of lipid zonation in NASH. In addition, we found increased hepatic expression of genes associated with remodeling the phospholipid membrane, release of arachidonic acid (AA) from the membrane, and production of eicosanoid species that promote inflammation and cell injury. The results of our immunohistochemistry analyses suggest that the zonal location of remodeling enzyme LPCAT2 plays a role in the change in spatial distribution for AA-containing lipids. This results in a cycle of AA-enrichment in pericentral hepatocytes, membrane release of AA, and generation of proinflammatory eicosanoids and may account for increased oxidative damage in pericentral regions in NASH. CONCLUSION: NAFLD is associated not only with lipid enrichment, but also with zonal changes of specific lipids and their associated metabolic pathways. This may play a role in the heterogeneous development of NAFLD. (Hepatology 2017;65:1165-1180).

Molecular Modeling Approach to Determine the Flory-Huggins Interaction Parameter for Polymer Miscibility Analysis.

In this work, we present a thorough procedure for estimating the Flory-Huggins χ-parameter for use in atomistic and mesoscale molecular simulations in computational materials science. In particular, we propose improvements upon traditional Flory-Huggins theory by implementing a Connolly volume normalization (CVN). We apply this technique to several test systems, including a blend of poly (epichlorohydrin) and poly (methyl acrylate), a blend of polyethylene glycol and poly (methyl methacrylate), a blend of polystyrene and deuterated polystyrene, and three molecular-weight variants (monomer, dimer, and trimer) of a triblock copolymer for use in multicompartment micelle applications. Our results demonstrate that the newly developed procedure offers high accuracy and efficiency in predicting the Flory-Huggins χ-parameter for miscibility analysis compared to traditional experimental and computational methods. There are still several factors that cause the magnitude of the χ-parameter to vary between simulations performed on molecular species with the same identity but different degrees of polymerization; although we discuss possible explanations for these factors, this is nonetheless a primary focus for further exploration into this new methodology.

Using extensional flow to reveal diverse aggregation landscapes for three IgG1 molecules.

Monoclonal antibodies (mAbs) currently dominate the biopharmaceutical sector due to their potency and efficacy against a range of disease targets. These proteinaceous therapeutics are, however, susceptible to unfolding, mis-folding, and aggregation by environmental perturbations. Aggregation thus poses an enormous challenge to biopharmaceutical development, production, formulation, and storage. Hydrodynamic forces have also been linked to aggregation, but the ability of different flow fields (e.g., shear and extensional flow) to trigger aggregation has remained unclear. To address this question, we previously developed a device that allows the degree of extensional flow to be controlled. Using this device we demonstrated that mAbs are particularly sensitive to the force exerted as a result of this flow-field. Here, to investigate the utility of this device to bio-process/biopharmaceutical development, we quantify the effects of the flow field and protein concentration on the aggregation of three mAbs. We show that the response surface of mAbs is distinct from that of bovine serum albumin (BSA) and also that mAbs of similar sequence display diverse sensitivity to hydrodynamic flow. Finally, we show that flow-induced aggregation of each mAb is ameliorated by different buffers, opening up the possibility of using the device as a formulation tool. Perturbation of the native state by extensional flow may thus allow identification of aggregation-resistant mAb candidates, their bio-process parameters and formulation to be optimized earlier in the drug-discovery pipeline using sub-milligram quantities of material.

Advanced multivariate data analysis to determine the root cause of trisulfide bond formation in a novel antibody-peptide fusion.

Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody-peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high-throughput (HT) micro-bioreactor system (AmbrTM 15) using a design of experiments (DoE) approach. The complex dataset was firstly analyzed through the development of a multiple linear regression model focusing solely on the DoE inputs and identified the temperature, pH and initial nutrient feed day as important process parameters influencing this quality attribute. To further scrutinize the dataset, a partial least squares model was subsequently built incorporating both on-line and off-line process parameters and enabled accurate predictions of the TSB concentration at harvest. Process parameters identified by the models to promote and suppress TSB formation were implemented on five 7 L bioreactors and the resultant TSB concentrations were comparable to the model predictions. This study demonstrates the ability of MVDA to enable predictions of the key performance drivers influencing TSB formation that are valid also upon scale-up. Biotechnol. Bioeng. 2017;114: 2222-2234. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

Does flood rhythm drive ecosystem responses in tropical riverscapes?

Biotic communities are shaped by adaptations from generations of exposure to selective pressures by recurrent and often infrequent events. In large rivers, floods can act as significant agents of change, causing considerable physical and biotic disturbance while often enhancing productivity and diversity. We show that the relative balance between these seemingly divergent outcomes can be explained by the rhythmicity, or predictability of the timing and magnitude, of flood events. By analyzing biological data for large rivers that span a gradient of rhythmicity in the Neotropics and tropical Australia, we find that systems with rhythmic annual floods have higher-fish species richness, more stable avian populations, and elevated rates of riparian forest production compared with those with arrhythmic flood pulses. Intensification of the hydrological cycle driven by climate change, coupled with reductions in runoff due to water extractions for human use and altered discharge from impoundments, is expected to alter the hydrologic rhythmicity of floodplain rivers with significant consequences for both biodiversity and productivity.

Evaluation of strategies to control Fab light chain dimer during mammalian expression and purification: A universal one-step process for purification of correctly assembled Fab.

Fabs are an important class of antibody fragment as both research reagents and therapeutic agents. There are a plethora of methods described for their recombinant expression and purification. However, these do not address the issue of excessive light chain production that forms light chain dimers nor do they describe a universal purification strategy. Light chain dimer impurities and the absence of a universal Fab purification strategy present persistent challenges for biotechnology applications using Fabs, particularly around the need for bespoke purification strategies. This study describes methods to address light chain dimer formation during Fab expression and identifies a novel CH 1 affinity resin as a simple and efficient one-step purification for correctly assembled Fab.

To 200,000 m/z and Beyond: Native Electron Capture Charge Reduction Mass Spectrometry Deconvolves Heterogeneous Signals in Large Biopharmaceutical Analytes.

Great progress has been made in the detection of large biomolecular analytes by native mass spectrometry; however, characterizing highly heterogeneous samples remains challenging due to the presence of many overlapping signals from complex ion distributions. Electron-capture charge reduction (ECCR), in which a protein cation captures free electrons without apparent dissociation, can separate overlapping signals by shifting the ions to lower charge states. The concomitant shift to higher m/z also facilitates the exploration of instrument upper m/z limits if large complexes are used. Here we perform native ECCR on the bacterial chaperonin GroEL and megadalton scale adeno-associated virus (AAV) capsid assemblies on a Q Exactive UHMR mass spectrometer. Charge reduction of AAV8 capsids by up to 90% pushes signals well above 100,000 m/z and enables charge state resolution and mean mass determination of these highly heterogeneous samples, even for capsids loaded with genetic cargo. With minor instrument modifications, the UHMR instrument can detect charge-reduced ion signals beyond 200,000 m/z. This work demonstrates the utility of ECCR for deconvolving heterogeneous signals in native mass spectrometry and presents the highest m/z signals ever recorded on an Orbitrap instrument, opening up the use of Orbitrap native mass spectrometry for heavier analytes than ever before.

Effects of traveling wave ion mobility separation on data independent acquisition in proteomics studies.

qTOF mass spectrometry and traveling wave ion mobility separation (TWIMS) hybrid instruments (q-TWIMS-TOF) have recently become commercially available. Ion mobility separation allows an additional dimension of precursor separation inside the instrument, without incurring an increase in instrument time. We comprehensively investigated the effects of TWIMS on data-independent acquisition on a Synapt G2 instrument. We observed that if fragmentation is performed post TWIMS, more accurate assignment of fragment ions to precursors is possible in data independent acquisition. This allows up to 60% higher proteome coverage and higher confidence of protein and peptide identifications. Moreover, the majority of peptides and proteins identified upon application of TWIMS span the lower intensity range of the proteome. It has also been demonstrated in several studies that employing IMS results in higher peak capacity of separation and consequently more accurate and precise quantitation of lower intensity precursor ions. We observe that employing TWIMS results in an attenuation of the detected ion current. We postulate that this effect is binary; sensitivity is reduced due to ion scattering during transfer into a high pressure "IMS zone", sensitivity is reduced due to the saturation of detector digitizer as a result of the IMS concentration effect. This latter effect limits the useful linear range of quantitation, compromising quantitation accuracy of high intensity peptides. We demonstrate that the signal loss from detector saturation and transmission loss can be deconvoluted by investigation of the peptide isotopic envelope. We discuss the origin and extent of signal loss and suggest methods to minimize these effects on q-TWIMS-TOF instrument in the light of different experimental designs and other IMS/MS platforms described previously.

Improving qualitative and quantitative performance for MS(E)-based label-free proteomics.

Label-free quantitation by data independent methods (for instance MS(E)) is growing in popularity due to the high technical reproducibility of mass spectrometry analysis. The recent introduction of Synapt hybrid instruments capable of incorporating ion mobility separation within mass spectrometry analysis now allows acquisition of high definition MS(E) data (HDMS(E)). HDMS(E) enables deeper proteome coverage and more confident peptide identifications when compared to MS(E), while the latter offers a higher dynamic range for quantitation. We have developed synapter as, a versatile tool to better evaluate the results of data independent acquisitions on Waters instruments. We demonstrate that synapter can be used to combine HDMS(E) and MS(E) data to achieve deeper proteome coverage delivered by HDMS(E) and more accurate quantitation for high intensity peptides, delivered by MS(E). For users who prefer to run samples exclusively in one mode, synapter allows other useful functionality like false discovery rate estimation, filtering on peptide match type and mass error, and filling missing values. Our software integrates with existing tools, thus permitting us to easily combine peptide quantitation information into protein quantitation by a range of different approaches.

Multi-Attribute Monitoring Method for Process Development of Engineered Antibody for Site-Specific Conjugation.

Antibody drug conjugates, a class of biotherapeutic proteins, have been extensively developed in recent years, resulting in new approvals and improved standard of care for cancer patients. Among the numerous strategies of conjugating cytotoxic payloads to monoclonal antibodies, insertion of a cysteine residue achieves a tightly controlled, site-specific drug to antibody ratio. Tailored analytical tools are required to direct the development of processes capable of manufacturing novel antibody scaffolds with the desired product quality. Here, we describe the development of a 12 min, mass-spectrometry-based method capable of monitoring four distinct quality attributes simultaneously: variations in the thiol state of the inserted cysteines, N-linked glycosylation, reduction of interchain disulfide bonds, and polypeptide fragmentation. This method provides new insight into the properties of the antibody intermediate and associated manufacturing processes. Oxidized thiol states are formed within the bioreactor, of which a variant containing an additional disulfide bond was produced and remained relatively constant throughout the fed-batch process; reduced thiol variants were introduced upon harvest. Nearly 20 percent of N-linked glycans contained sialic acid, substantially higher than anticipated for wildtype IgG1. Lastly, previously unreported polypeptide fragmentation sites were identified in the C239i constant domain, and the relationship between fragmentation and glycoform were explored. This work illustrates the utility of applying a high-throughput liquid chromatography-mass spectrometry multi-attribute monitoring method to support the development of engineered antibody scaffolds.

Next-generation cell line selection methodology leveraging data lakes, natural language generation and advanced data analytics.

Cell line development is an essential stage in biopharmaceutical development that often lies on the critical path. Failure to fully characterise the lead clone during initial screening can lead to lengthy project delays during scale-up, which can potentially compromise commercial manufacturing success. In this study, we propose a novel cell line development methodology, referenced as CLD 4, which involves four steps enabling autonomous data-driven selection of the lead clone. The first step involves the digitalisation of the process and storage of all available information within a structured data lake. The second step calculates a new metric referenced as the cell line manufacturability index (MI CL) quantifying the performance of each clone by considering the selection criteria relevant to productivity, growth and product quality. The third step implements machine learning (ML) to identify any potential risks associated with process operation and relevant critical quality attributes (CQAs). The final step of CLD 4 takes into account the available metadata and summaries all relevant statistics generated in steps 1-3 in an automated report utilising a natural language generation (NLG) algorithm. The CLD 4 methodology was implemented to select the lead clone of a recombinant Chinese hamster ovary (CHO) cell line producing high levels of an antibody-peptide fusion with a known product quality issue related to end-point trisulfide bond (TSB) concentration. CLD 4 identified sub-optimal process conditions leading to increased levels of trisulfide bond that would not be identified through conventional cell line development methodologies. CLD 4 embodies the core principles of Industry 4.0 and demonstrates the benefits of increased digitalisation, data lake integration, predictive analytics and autonomous report generation to enable more informed decision making.

Stochastic assembly of biomacromolecular complexes: impact and implications on charge interpretation in native mass spectrometry.

Native mass spectrometry is a potent method for characterizing biomacromolecular assemblies. A critical aspect to extracting accurate mass information is the correct inference of the ion ensemble charge states. While a variety of experimental strategies and algorithms have been developed to facilitate this, virtually all approaches rely on the implicit assumption that any peaks in a native mass spectrum can be directly attributed to an underlying charge state distribution. Here, we demonstrate that this paradigm breaks down for several types of macromolecular protein complexes due to the intrinsic heterogeneity induced by the stochastic nature of their assembly. Utilizing several protein assemblies of adeno-associated virus capsids and ferritin, we demonstrate that these particles can produce a variety of unexpected spectral appearances, some of which appear superficially similar to a resolved charge state distribution. When interpreted using conventional charge inference strategies, these distorted spectra can lead to substantial errors in the calculated mass (up to ∼5%). We provide a novel analytical framework to interpret and extract mass information from these spectra by combining high-resolution native mass spectrometry, single particle Orbitrap-based charge detection mass spectrometry, and sophisticated spectral simulations based on a stochastic assembly model. We uncover that these mass spectra are extremely sensitive to not only mass heterogeneity within the subunits, but also to the magnitude and width of their charge state distributions. As we postulate that many protein complexes assemble stochastically, this framework provides a generalizable solution, further extending the usability of native mass spectrometry in the characterization of biomacromolecular assemblies.

Genomic variation among contemporary Pseudomonas aeruginosa isolates from chronically infected cystic fibrosis patients.

The airways of individuals with cystic fibrosis (CF) often become chronically infected with unique strains of the opportunistic pathogen Pseudomonas aeruginosa. Several lines of evidence suggest that the infecting P. aeruginosa lineage diversifies in the CF lung niche, yet so far this contemporary diversity has not been investigated at a genomic level. In this work, we sequenced the genomes of pairs of randomly selected contemporary isolates sampled from the expectorated sputum of three chronically infected adult CF patients. Each patient was infected by a distinct strain of P. aeruginosa. Single nucleotide polymorphisms (SNPs) and insertions/deletions (indels) were identified in the DNA common to the paired isolates from different patients. The paired isolates from one patient differed due to just 1 SNP and 8 indels. The paired isolates from a second patient differed due to 54 SNPs and 38 indels. The pair of isolates from the third patient both contained a mutS mutation, which conferred a hypermutator phenotype; these isolates cumulatively differed due to 344 SNPs and 93 indels. In two of the pairs of isolates, a different accessory genome composition, specifically integrated prophage, was identified in one but not the other isolate of each pair. We conclude that contemporary isolates from a single sputum sample can differ at the SNP, indel, and accessory genome levels and that the cross-sectional genomic variation among coeval pairs of P. aeruginosa CF isolates can be comparable to the variation previously reported to differentiate between paired longitudinally sampled isolates.

Spatial variation in egg size and egg number reflects trade-offs and bet-hedging in a freshwater fish.

1. Maternal reproductive investment is thought to reflect a trade-off between offspring size and fecundity, and models generally predict that mothers inhabiting adverse environments will produce fewer, larger offspring. More recently, the importance of environmental unpredictability in influencing maternal investment has been considered, with some models predicting that mothers should adopt a diversified bet-hedging strategy whilst others a conservative bet-hedging strategy. 2. We explore spatial egg size and fecundity patterns in the freshwater fish southern pygmy perch (Nannoperca australis) that inhabits a diversity of streams along gradients of environmental quality, variability and predictability. 3. Contrary to some predictions, N. australis populations inhabiting increasingly harsh streams produced more numerous and smaller eggs. Furthermore, within-female egg size variability increased as environments became more unpredictable. 4. We argue that in harsh environments or those prone to physical disturbance, sources of mortality are size independent with offspring size having only a minor influence on offspring fitness. Instead, maternal fitness is maximized by producing many small eggs, increasing the likelihood that some offspring will disperse to permanent water. We also provide empirical support for diversified bet-hedging as an adaptive strategy when future environmental quality is uncertain and suggest egg size may be a more appropriate fitness measure in stable environments characterized by size-dependent fitness. These results likely reflect spatial patterns of adaptive plasticity and bet-hedging in response to both predictable and unpredictable environmental variance and highlight the importance of considering both trait averages and variance. 5. Reproductive life-history traits can vary predictably along environmental gradients. Human activity, such as the hydrological modification of natural flow regimes, alters the form and magnitude of these gradients, and this can have both ecological and evolutionary implications for biota adapted to now non-existent natural environmental heterogeneity.