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Lee, J. J.

Publications and source records attributed to Lee, J. J..

At least 37 records · Page 2Linked to original sources

Bio-Accelerated Weathering of Ultramafic Minerals with Gluconobacter oxydans

Ultramafic rocks are an abundant source of cations for CO2 mineralization (e.g., Mg) and elements for sustainability technologies (e.g., Ni, Cr, Mn, Co, Al). However, there is no industrially useful process for dissolving ultramafic materials to release cations for CO2 sequestration or mining them for energy-critical elements. Weathering of ultramafic rocks by rainwater, release of metal cations, and subsequent CO2 mineralization already naturally sequesters CO2 from the atmosphere, but this natural process will take thousands to hundreds of thousands of years to remove excess anthropogenic CO2, far too late to deal with global warming that will happen over the next century. Mechanical acceleration of weathering by grinding can accelerate cation release but is prohibitively expensive. In this article we show that gluconic acid-based lixiviants produced by the mineral-dissolving microbe Gluconobacter oxydans accelerate leaching of Mg2+ by 20x over deionized water, and that leaching of Mg, Mn, Fe, Co, and Ni further improves by 73% from 24 to 96 hours. At low pulp density (1%) the G. oxydans biolixiviant is only 6% more effective than gluconic acid. But, at 60% pulp density the G. oxydans biolixiviant is 3.2x more effective than just gluconic acid. We demonstrate that biolixiviants made with cellulosic hydrolysate are not significantly worse than biolixiviants made with glucose, dramatically improving the feedstock available for bioleaching. Finally, we demonstrate that we can reduce the number of carbon atoms in the biolixiviant feedstock (e.g., glucose or cellulosic hydrolysate) needed to release one Mg2+ ion and mineralize one atom of carbon from CO2 from 525 to 1.

bioengineering↗

The brain's "dark energy" puzzle upgraded: FDG uptake, delivery and phosphorylation, and their coupling with resting-state brain activity

The brains resting-state energy consumption is expected to be mainly driven by spontaneous activity. In our previous work, we extracted a wide range of features from resting-state fMRI (rs-fMRI), and used them to predict [18F]FDG PET SUVR as a proxy of glucose metabolism. Here, we expanded upon our previous effort by estimating [18F]FDG kinetic parameters according to Sokoloffs model, i.e., Ki (irreversible uptake rate), K1 (delivery), k3 (phosphorylation), in a large healthy control group. The parameters spatial distribution was described at a high spatial resolution. We showed that while K1 is the least redundant, there are relevant differences between Ki and k3 (occipital cortices, cerebellum and thalamus). Using multilevel modeling, we investigated how much of the regional variability of [18F]FDG parameters could be explained by a combination of rs-fMRI variables only, or with the addition of cerebral blood flow (CBF) and metabolic rate of oxygen (CMRO2), estimated from 15O PET data. We found that combining rs-fMRI and CMRO2 led to satisfactory prediction of individual Ki variance (45%). Although more difficult to describe, Ki and k3 were both most sensitive to local rs-fMRI variables, while K1 was sensitive to CMRO2. This work represents the most comprehensive assessment to date of the complex functional and metabolic underpinnings of brain glucose consumption.

neuroscience↗

Hyperglycemia selectively increases cerebral non-oxidative glucose consumption without affecting blood flow

Multiple studies have shown that hyperglycemia increases the cerebral metabolic rate of glucose (CMRglc) in subcortical white matter. This observation remains unexplained. Using positron emission tomography (PET) and euinsulinaemic glucose clamps, we found, for the first time, that acute hyperglycemia increases non-oxidative CMRglc (i.e., aerobic glycolysis (AG)) in subcortical white mater as well as in medial temporal lobe structures, cerebellum and brainstem, all areas with low euglycemic CMRglc. Surprisingly, hyperglycemia did not change regional cerebral blood flow (CBF), the cerebral metabolic rate of oxygen (CMRO2), or the blood-oxygen-level-dependent (BOLD) response. Regional gene expression data reveal that brain regions where CMRglc increased have greater expression of hexokinase 2 (HK2). Simulations of glucose transport revealed that, unlike hexokinase 1, HK2 is not saturated at euglycemia, thus accommodating increased AG during hyperglycemia.

neuroscience↗

Myeloid progenitor dysregulation fuels immunosuppressive macrophages in tumors

ABSTRACTMonocyte-derived macrophages (mo-macs) drive immunosuppression in the tumor microenvironment (TME) and tumor-enhanced myelopoiesis in the bone marrow (BM) fuels these populations. Here, we performed paired transcriptome and chromatin analysis over the continuum of BM myeloid progenitors, circulating monocytes, and tumor-infiltrating mo-macs in mice and in patients with lung cancer to identify myeloid progenitor programs that fuel pro-tumorigenic mo-macs. Analyzing chromatin accessibility and histone mark changes, we show that lung tumors prime accessibility for Nfe2l2 (NRF2) in BM myeloid progenitors as a cytoprotective response to oxidative stress. NRF2 activity is sustained and increased during monocyte differentiation into mo-macs in the lung TME to regulate oxidative stress, in turn promoting metabolic adaptation, resistance to cell death, and contributing to immunosuppressive phenotype. NRF2 genetic deletion and pharmacological inhibition significantly reduced mo-macs survival and immunosuppression in the TME, enabling NK and T cell therapeutic antitumor immunity and synergizing with checkpoint blockade strategies. Altogether, our study identifies a targetable epigenetic node of myeloid progenitor dysregulation that sustains immunoregulatory mo-macs in the TME.

immunology↗

Bacteriophage {Phi}21s receptor-binding protein evolves new functions through destabilizing mutations that generate non-genetic phenotypic heterogeneity

How viruses evolve to expand their host range is a major question with implications for predicting the next pandemic. Gain-of-function experiments have revealed that host-range expansions can occur through relatively few mutations in viral receptor-binding proteins, and the search for molecular mechanisms that explain such expansions are underway. Previous research on expansions of receptor use in bacteriophage {lambda} has shown that mutations that destabilize {lambda}s receptor-binding protein cause the receptor-binding protein to fold into new conformations that can utilize novel receptors but have weakened thermostability. These observations led us to hypothesize that other viruses may take similar paths to expand their host range. Here, we find support for our hypothesis by studying another virus, bacteriophage 21 ({Phi}21), which evolves to use two new host receptors within two weeks of laboratory evolution. By measuring the thermodynamic stability of {Phi}21 and its descendants, we show that, as {Phi}21 evolves to use new receptors and expands its host range, it becomes less stable and produces viral particles that are genetically identical but vary in their thermostabilities. Next, we show that this non-genetic heterogeneity between particles is directly associated with receptor use innovation, as phage particles with more derived receptor use capabilities are more unstable and decay faster. Lastly, by manipulating the expression of protein chaperones during {Phi}21 infection, we demonstrate that heterogeneity in thermostability and receptor use breadth of phage particles is directly related to the folding of phage proteins into different conformers. Altogether, our results provide support for the hypothesis that viruses can evolve new receptor-use tropisms through mutations that destabilize the receptor-binding protein and produce multiple protein conformers.

evolutionary biology↗

TPPB modulates PKC activity to attenuate neuroinflammation and ameliorate experimental multiple sclerosis

Protein kinase C (PKC) plays a key role in modulating the activities of the innate immune cells of the central nervous system (CNS). A delicate balance between pro-inflammatory and regenerative activities by microglia and CNS-associated macrophages is necessary for the proper functioning of the CNS. Thus, a maladaptive activation of these CNS innate immune cells results in neurodegeneration and demyelination associated with various neurologic disorders, such as multiple sclerosis (MS) and Alzheimers disease. Prior studies have demonstrated that modulation of PKC activity by bryostatin-1 (bryo-1) and its analogs (bryologs) attenuates the pro-inflammatory processes by microglia/CNS macrophages and alleviates the neurologic symptoms in experimental autoimmune encephalomyelitis (EAE), an MS animal model. Here, we demonstrate that (2S,5S)-(E,E)-8-(5-(4-(trifluoromethyl)phenyl)-2,4-pentadienoylamino)benzolactam (TPPB), a structurally distinct PKC modulator, has a similar effect to bryo-1 on CNS innate immune cells both in vitro and in vivo, attenuating neuroinflammation and resulting in CNS regeneration and repair. This study identifies a new structural class of PKC modulators, which can therapeutically target CNS innate immunity as a strategy to treat neuroinflammatory and neurodegenerative disorders.

immunology↗

Parsing digital or analogue TCR performance through piconewton forces

{beta} T-cell receptors (TCRs) recognize aberrant peptides bound to major histocompatibility complex molecules (pMHCs) on unhealthy cells, amplifying specificity and sensitivity through physical load placed on the TCR-pMHC bond during immunosurveillance. To understand this mechanobiology, TCRs stimulated by abundantly and sparsely arrayed epitopes (NP366-374 /Db and PA224-233/Db, respectively) following in vivo influenza A virus infection were studied with optical tweezers. While certain NP repertoire CD8 T lymphocytes require many ligands for activation, others are digital, needing just few. Conversely, all PA TCRs perform digitally, exhibiting pronounced bond lifetime increases through sustained, energizing volleys of structural transitioning. Optimal digital performance is superior in vivo, correlating with ERK phosphorylation, CD3 loss, and activation marker upregulation in vitro. Given neoantigen array paucity, digital TCRs are likely critical for immunotherapies. One Sentence SummaryQuality of ligand recognition in a T-cell repertoire is revealed through application of physical load on clonal T-cell receptor (TCR)-pMHC bonds

immunology↗

A novel Bayesian model for assessing intratumor heterogeneity of tumor infiltrating leukocytes with multi-region gene expression sequencing

Intratumor heterogeneity (ITH) of tumor-infiltrated leukocytes (TILs) is an important phenomenon of cancer biology with potentially profound clinical impacts. Multiregion gene expression sequencing data provide a promising opportunity that allows for explorations of TILs and their intratumor heterogeneity for each subject. Although several existing methods are available to infer the proportions of TILs, considerable methodological gaps exist for evaluating intratumor heterogeneity of TILs with multi-region gene expression data. Here, we develop ICeITH, immune cell estimation reveals intratumor heterogeneity, a Bayesian hierarchical model that borrows cell type profiles as prior knowledge to decompose mixed bulk data while accounting for the within-subject correlations among tumor samples. ICeITH quantifies intratumor heterogeneity by the variability of targeted cellular compositions. Through extensive simulation studies, we demonstrate that ICeITH is more accurate in measuring relative cellular abundance and evaluating intratumor heterogeneity compared with existing methods. We also assess the ability of ICeITH to stratify patients by their intratumor heterogeneity score and associate the estimations with the survival outcomes. Finally, we apply ICeITH to two multi-region gene expression datasets from lung cancer studies to classify patients into different risk groups according to the ITH estimations of targeted TILs that shape either pro- or anti-tumor processes. In conclusion, ICeITH is a useful tool to evaluate intratumor heterogeneity of TILs from multi-region gene expression data.

bioinformatics↗

Constraints on Lanthanide Separation by Selective Biosorption

Rare Earth Elements (REE) are essential ingredients of sustainable energy technologies1-5, but separation of lanthanides is considered one of the hardest problems in chemistry today6. Biosorption, where molecules adsorb to the surface of biological materials, offers a sustainable alternative to environmentally harmful solvent extractions currently used for REE separations. The REE-biosorption capabilities of some microorganisms already allow for REE separations that under specialized conditions are competitive with solvent extractions7. Our recent work has discovered the genetic basis for REE biosorption selectivity8. However, it is unclear if the small changes to selectivity produced by changes to single genetic loci could allow biosorption to leapfrog existing REE separation technologies. In this article we present three models of lanthanide separation by biosorption and desorption. The first model shows that if a biosorbing microbe behaves as it if has a single type of binding site with small preference for one lanthanide, then the small changes in selectivity produced by changes to a single genetic locus could reduce the length of a separation process by {approx} 25%. Large multi-locus gene edits could reduce a separation process length by almost 90%. On the other hand, if the microbe contains multiple sites each with a distinct preference for an individual lanthanide, then separations become challenging and larger genetic edits would be needed to enable high purity. However, even if these large genetic edits are not possible, high purity separations could still be possible by combining multiple microbes, each with small increases in selectivity, with the first designed to enrich for the target lanthanide, while subsequent microbes are designed to remove contaminants.

synthetic biology↗

PKC modulator bryostatin-1 therapeutically targets CNS innate immunity to attenuate neuroinflammation and promote remyelination

In multiple sclerosis (MS), microglia and macrophages within the central nervous system (CNS) play an important role in determining the balance between myelin repair and demyelination/neurodegeneration. Phagocytic and regenerative functions of these CNS innate immune cells support remyelination, whereas chronic and maladaptive inflammatory activation promotes lesion expansion and disability, particularly in the progressive forms of MS. No currently approved drugs convincingly target microglia and macrophages within the CNS, contributing to the critical lack of therapies promoting remyelination and slowing progression in MS. Here, we found that the protein kinase C (PKC)-modulating drug bryostatin-1 (bryo-1), a CNS-penetrant compound with an established human safety profile, produces a shift in microglia and CNS macrophage transcriptional programs from pro-inflammatory to regenerative phenotypes, both in vitro and in vivo. Treatment of microglia with bryo-1 prevented the activation of neurotoxic astrocytes while stimulating scavenger pathways, phagocytosis, and secretion of factors that promote oligodendrocyte differentiation. In line with these findings, systemic treatment with bryo-1 augmented remyelination following a focal demyelinating injury in vivo. Our results demonstrate the potential of bryo-1 and functionally related PKC modulators as myelin regenerative and neuroprotective agents in MS and other neurologic diseases through therapeutic targeting of microglia and CNS-associated macrophages. One Sentence SummaryPKC modulation in CNS innate immune cells favors the activation of a beneficial phenotype that promotes myelin regeneration and neuroprotection.

neuroscience↗

eIF2B Activator Rescues Neonatal Lethality of an eIF2Bα Sugar Phosphate Binding Mutation Associated with Vanishing White Matter Disease

eIF2B is a decameric guanine nucleotide exchange factor (GEF) that is essential for protein synthesis and a key effector of the integrated stress response (ISR). Hypomorphic mutations in any of the eIF2B subunits are associated with Vanishing White Matter Disease (VWM), a leukodystrophy characterized by ISR activation and white matter loss. Here, we showed that the VWM-associated N208Y eIF2B mutation, which abolishes sugar phosphate binding, led to a drastic reduction in its level in cells and concomitant ISR activation. We found that N208Y homozygous mice are small and die shortly after birth. Remarkably, continuous availability of 2BAct, a small molecule eIF2B activator, in food rescued the lethality and significantly extended their lifespan. 2BAct-maintained N208Y homozygous mice, however, developed motor deficits and loss of myelin with age. As is the case for milder VWM models, ISR induction was restricted to the central nervous system in treated animals. Upon 2BAct withdrawal, adult mutant mice deteriorated quickly, the ISR was induced in all peripheral tissues tested and resulted in high levels of circulating FGF21 and GDF15. This model provides a novel platform to study the impact of ISR activation across tissues with temporal control.

neuroscience↗

Rapid bacteria-phage coevolution drives the emergence of multi-scale networks

Interactions between species have catalyzed the evolution of multiscale ecological networks-including both nested and modular elements that regulate the function of diverse communities. One common assumption is that such complex pattern formation requires long evolutionary timescales, spatial isolation, or other exogenous processes. Here we show that multiscale network structure can evolve rapidly under simple ecological conditions without spatial structure. In just 21 days of laboratory coevolution, Escherichia coli and bacteriophage {Phi}21 coevolve and diversify to form elaborate cross-infection networks. By measuring [~]10,000 phage-bacteria infections and testing the genetic basis of interactions, we identify the mechanisms that create each component of the multiscale pattern. Initially, nested patterns form through an arms race where hosts successively lose the original receptor (LamB) and phages evolve to use a second (OmpC) and then a third (OmpF) receptor. Next, modules form when the cost of losing the third receptor, OmpF, increases and bacteria evolve resistance mutations that modify the OmpF receptors extramembrane loops. In turn, phages evolve adaptations that facilitate specialized interactions with different OmpF variants. Nestedness reemerges within modules as bacteria evolve increased resistance and phages enhance infectivity against module-specific receptor variants. Our results demonstrate how multiscale networks evolve in parasite-host systems, illustrating Darwins idea that simple adaptive processes can generate entangled banks of ecological interactions.

evolutionary biology↗

A genome-wide association study of the Neuroticism general factor

We applied structural equation modeling to conduct a genome-wide association study (GWAS) of the general factor measured by a neuroticism questionnaire administered to[~] 380,000 participants in the UK Biobank. We categorized significant genetic variants as acting either through the neuroticism general factor, through other factors measured by the questionnaire, or through paths independent of any factor. Regardless of this categorization, however, significant variants tended to show concordant associations with all items. Bioinformatic analysis showed that the variants associated with the neuroticism general factor disproportionately lie near or within genes expressed in the brain. Enriched gene sets pointed to an underlying biological basis associated with brain development, synaptic function, and behaviors in mice indicative of fear and anxiety. Psychologists have long asked whether psychometric common factors are merely a convenient summary of correlated variables or reflect coherent causal entities with a partial biological basis, and our results provide some support for the latter interpretation. Further research is needed to determine the extent to which causes resembling common factors operate alongside other mechanisms to generate the correlational structure of personality.

genetics↗

A new framework for metabolic connectivity mapping using bolus FDG PET and kinetic modelling

PurposeMetabolic connectivity (MC) has been previously proposed as the covariation of static [18F]FDG PET images across participants, which we call across-individual MC (ai-MC). In few cases, MC has also been inferred from dynamic [18F]FDG signals, similarly to fMRI functional connectivity (FC), which we term within-individual MC (wi-MC). The validity and interpretability of both MC approaches is an important open issue. Here we reassess this topic, aiming to 1) develop a novel methodology for wi-MC estimation; 2) compare ai-MC maps obtained using different [18F]FDG parameters (K1, i.e. tracer transport rate, k3, i.e. phosphorylation rate, Ki, i.e. tracer uptake rate, and the standardized uptake value ratio, SUVR); 3) assess the interpretability of ai-MC and wi-MC in comparison to structural and functional connectivity (FC) measures. MethodsWe analyzed dynamic [18F]FDG data from 54 healthy adults using kinetic modelling to quantify the macro- and microparameters describing the tracer behavior (i.e. Ki, K1, k3). We also calculated SUVR. From the across-individual correlation of SUVR, Ki, K1, k3, we obtained four different ai-MC matrices. A new approach based on Euclidean distance was developed to calculate wi-MC from PET time-activity curves. ResultsWe identified Euclidean similarity as the most appropriate metric to calculate wi-MC. ai-MC networks changed with different [18F]FDG parameters (k3 MC vs. SUVR MC, r = 0.44). We found that wi-MC and ai-MC matrices are dissimilar (maximum r = 0.37), and that the match with FC is higher for wi-MC (Dice similarity: 0.47-0.63) than for ai-MC (0.24-0.39). ConclusionOur data demonstrate that individual-level MC from dynamic [18F]FDG data using Euclidean similarity is feasible and yields interpretable matrices that bear similarity to resting-state fMRI FC measures.

bioengineering↗

Transcriptomic Profiling of Plasma Extracellular Vesicles Enables Reliable Annotation of the Cancer-specific Transcriptome and Molecular Subtype

Longitudinal monitoring of patients with advanced cancers is crucial to evaluate both disease burden and treatment response. Current liquid biopsy approaches mostly rely on the detection of DNA-based biomarkers. However, plasma RNA analysis can unleash tremendous opportunities for tumor state interrogation and molecular subtyping. Through the application of deep learning algorithms to the deconvolved transcriptomes of RNA within plasma extracellular vesicles (evRNA), we successfully predict consensus molecular subtypes in metastatic colorectal cancer patients. We further demonstrate the ability to monitor changes in transcriptomic subtype under treatment selection pressure and identify molecular pathways in evRNA associated with recurrence. Our approach also identified expressed gene fusions and neoepitopes from evRNA. These results demonstrate the feasibility of transcriptomic-based liquid biopsy platforms for precision oncology approaches, spanning from the longitudinal monitoring of tumor subtype changes to identification of expressed fusions and neoantigens as cancer-specific therapeutic targets, sans the need for tissue-based sampling. Statement of significanceWe have developed an approach to interrogate changes in cancer molecular subtypes and differentially expressed genes, through the analysis and deconvolution of RNA sequencing of plasma EVs. Serial analyses of tumor-encoded transcriptomes in liquid biopsies can enable facile cancer detection and monitor for recurrences and therapy-induced tumor evolution.

cancer biology↗

N-terminal acetylation shields proteins from degradation and promotes age-dependent motility and longevity

Most eukaryotic proteins are N-terminally acetylated, but the functional impact on a global scale has remained obscure. Using genome-wide CRISPR knockout screens in human cells, we reveal a strong genetic dependency between a major N-terminal acetyltransferase and specific ubiquitin ligases. Biochemical analyses uncover that both the ubiquitin ligase complex UBR4-KCMF1 and the acetyltransferase NatC recognize proteins bearing an unacetylated N-terminal methionine followed by a hydrophobic residue. NatC KO-induced protein degradation and phenotypes are reversed by UBR knockdown, demonstrating the central cellular role of this interplay. We reveal that loss of Drosophila NatC is associated with male sterility, reduced longevity, and age-dependent loss of motility due to developmental muscle defects. Remarkably, muscle-specific overexpression of UbcE2M, one of the proteins targeted for NatC KO mediated degradation, suppresses defects of NatC deletion. In conclusion, NatC-mediated N-terminal acetylation acts as a protective mechanism against protein degradation, which is relevant for increased longevity and motility. In BriefVarland, Silva et al. define that a major cellular role of N-terminal acetylation is shielding proteins from proteasomal degradation by specific ubiquitin ligases. The human N-terminal acetyltransferase NatC protects the neddylation regulator UBE2M from degradation, while overexpression of Drosophila UBE2M/UbcE2M rescues the longevity and motility defects of NatC deletion. HighlightsO_LIN-terminal acetylation by NatC protects proteins from degradation, including UBE2M C_LIO_LIUBR4-KCMF1 targets unacetylated N-terminal Met followed by a hydrophobic residue C_LIO_LIDrosophila NatC is required for adult longevity and motility in elderly C_LIO_LIOverexpression of UBE2M/UbcE2M suppresses Drosophila NatC deletion phenotypes C_LI

molecular biology↗

Enhanced capillary pumping using open-channel capillary trees with integrated paper pads

The search for efficient capillary pumping has led to two main directions for investigation: first, assembly of capillary channels to provide high capillary pressures, and second, imbibition in absorbing fibers or paper pads. In the case of open microfluidics (i.e., channels where the top boundary of the fluid is in contact with air instead of a solid wall), the coupling between capillary channels and paper pads unites the two approaches and provides enhanced capillary pumping. In this work, we investigate the coupling of capillary trees-- networks of channels mimicking the branches of a tree--with paper pads placed at the extremities of the channels, mimicking the small capillary networks of leaves. It is shown that high velocities and flow rates (7 mm/s or 13.1 {micro}L/s) for more than 30 seconds using 50% (v/v) isopropyl alcohol, which has a 3-fold increase in viscosity in comparison to water; 6.5 mm/s or 12.1 {micro}L/s for more than 55 seconds with pentanol, which has an 3.75-fold increase in viscosity in comparison to water; >3.5 mm/s or 6.5 {micro}L/s for more than 150 seconds with nonanol, which has an 11-fold increase in viscosity in comparison to water) can be reached in the root channel, enabling higher sustained flow rates than that of capillary trees alone.

bioengineering↗

Comparison of bacterial suppression by phage cocktails, dual-receptor generalists, and coevolutionarily trained phages

The evolution and spread of antibiotic resistant bacteria have renewed interest in phage therapy, the use of bacterial viruses (phages) to combat bacterial infections. The delivery of phages in cocktails where constituent phages target different modalities (e.g., receptors) may improve treatment outcomes by making it more difficult for bacteria to evolve resistance. However, the multipartite nature of cocktails may lead to unintended evolutionary and ecological outcomes. Here, we compare a 2-phage cocktail with a largely unconsidered group of phages: generalists that can infect through multiple, independent receptors. We find that both generalists and cocktails that target the same receptors suppress bacteria similarly for ~2 d. Yet a "trained" generalist phage, which previously adapted to its host via 28 d of coevolution, demonstrated superior suppression. To understand why the trained generalist was more effective, we measured the resistance of bacteria against each of our phages. We find that, when bacteria were assailed by 2 phages in the cocktail, they evolved mutations in manXYZ, a host inner-membrane transporter that {lambda} uses to move its DNA across the periplasmic space and into the cell for infection. This provided crossresistance against the cocktail and untrained generalist. However, these mutations were ineffective at blocking the trained generalist because, through coevolutionary training, it evolved to bypass manXYZ resistance. The trained generalists past experiences in training make it exceedingly difficult for bacteria to evolve resistance, further demonstrating the utility of coevolutionary phage training for improving the therapeutic properties of phages.

evolutionary biology↗