Pair Of Hosts Research Articles

Network Latency and Application Performance Aware Cluster Scheduling in Data Centers

Data-center-based cloud computing has revolutionized the way businesses use computing infrastructure. Instead of building their own data centers, companies rent computing resources and deploy their applications on cloud hardware. Providing customers with well-defined application performance guarantees is of paramount importance. A user's application performance is subject to the constraints of the resources it has been allocated and to the impact of the network conditions in the data center. Given the network latency variability observed in data centers, applications' performance is also determined by their placement within the data center. We present NoMora, a cluster scheduling architecture whose core is represented by a latency-driven, application-performance-aware cluster scheduling policy. The policy places the tasks of an application taking into account the expected performance based on the measured network latency between pairs of hosts in the data center. If a tenant's application experiences increased network latency, and thus lower application performance, their application may be migrated to a better placement. Experiments on a testbed and in simulations show that our architecture improves the overall average application performance by up to 32.5 and 42 percent, respectively, demonstrating that application performance can be improved by exploiting the relationship between network latency and application performance.

Predicting Segregation Energy in Single Atom Alloys Using Physics and Machine Learning.

Single atom alloys (SAAs) show great promise as catalysts for a wide variety of reactions due to their tunable properties, which can enhance the catalytic activity and selectivity. To design SAAs, it is imperative for the heterometal dopant to be stable on the surface as an active catalytic site. One main approach to probe SAA stability is to calculate surface segregation energy. Density functional theory (DFT) can be applied to investigate the surface segregation energy in SAAs. However, DFT is computationally expensive and time-consuming; hence, there is a need for accelerated frameworks to screen metal segregation for new SAA catalysts across combinations of metal hosts and dopants. To this end, we developed a model that predicts surface segregation energy using machine learning for a series of SAA periodic slabs. The model leverages elemental descriptors and features inspired by the previously developed bond-centric model. The initial model accurately captures surface segregation energy across a diverse series of FCC-based SAAs with various surface facets and metal–host pairs. Following our machine learning methodology, we expanded our analysis to develop a new model for SAAs formed from FCC hosts with FCC, BCC, and HCP dopants. Our final, five-feature model utilizes second-order polynomial kernel ridge regression. The model is able to predict segregation energies with a high degree of accuracy, which is due to its physically motivated features. We then expanded our data set to test the accuracy of the five features used. We find that the retrained model can accurately capture Eseg trends across different metal hosts and facets, confirming the significance of the features used in our final model. Finally, we apply our pretrained model to a series of Ir- and Pd-based SAA cuboctahedron nanoparticles (NPs), ranging in size and FCC dopants. Remarkably, our model (trained on periodic slabs) accurately predicts the DFT segregation energies of the SAA NPs. The results provide further evidence supporting the use of our model as a general tool for the rapid prediction of SAA segregation energies. By creating a framework to predict the metal segregation from bulk surfaces to NPs, we can accelerate the SAA catalyst design while simultaneously unraveling key physicochemical properties driving thermodynamic stabilization of SAAs.

Integrating Quantum Simulation for Quantum-Enhanced Classical Network Emulation

We describe a method of investigating the near-term potential of quantum communication technology for communication networks from the perspective of current networks. For this, we integrate an instance of the quantum network simulator QuNetSim at the link layer into the communication network emulator ComNetsEmu. This novel augmented version of ComNetsEmu is thereby enabled to run arbitrary quantum protocols between any directly connected pair of network hosts. To give an example of the proposed method, we implement the link layer method of generating and storing entanglement while idle, to accelerate data transmission at later times using superdense coding.

Imaging Techniques for Detecting Prokaryotic Viruses in Environmental Samples.

Viruses are the most abundant biological entities on Earth with an estimate of 1031 viral particles across all ecosystems. Prokaryotic viruses—bacteriophages and archaeal viruses—influence global biogeochemical cycles by shaping microbial communities through predation, through the effect of horizontal gene transfer on the host genome evolution, and through manipulating the host cellular metabolism. Imaging techniques have played an important role in understanding the biology and lifestyle of prokaryotic viruses. Specifically, structure-resolving microscopy methods, for example, transmission electron microscopy, are commonly used for understanding viral morphology, ultrastructure, and host interaction. These methods have been applied mostly to cultivated phage–host pairs. However, recent advances in environmental genomics have demonstrated that the majority of viruses remain uncultivated, and thus microscopically uncharacterized. Although light- and structure-resolving microscopy of viruses from environmental samples is possible, quite often the link between the visualization and the genomic information of uncultivated prokaryotic viruses is missing. In this minireview, we summarize the current state of the art of imaging techniques available for characterizing viruses in environmental samples and discuss potential links between viral imaging and environmental genomics for shedding light on the morphology of uncultivated viruses and their lifestyles in Earth’s ecosystems.

Load balancing with traffic isolation in data center networks

The topologies of current data center networks are typically multi-rooted trees (e.g. leaf–spine) with rich parallel paths between any pair of hosts. Recent progress has demonstrated that effective load balancing can fully utilize these parallel paths to speed up data transfer. Nonetheless, the existing load balancing designs are agnostic to the heterogeneous datacenter traffic, i.e., a mass of delay-sensitive short flows mix with a handful of throughput-oriented long flows, and casually reroute these flows regardless of path condition, thus resulting in frequent flow collisions. The short flows suffer from the problem of large queuing delay due to colliding with long flows, while the frequent collisions between long flows lead to low network utilization and serious throughput degradation. To address these inefficiencies, we propose an isolation-based load balancing scheme, namely ILB, which perceives flow collisions and dynamically isolates the long flows from short flows. Specifically, when a long flow collides with short flows in the same path, it immediately switches to another path unused by short flows to help the short ones in the previous path complete quickly. When short flows disappear, the long flow quickly occupies all its available paths to achieve high throughput. Moreover, ILB is only deployed on the leaf switch without modifying the end-host and spine switch. Experimental results of NS3 simulations show that ILB respectively reduces the average and tail flow completion time for short flows by up to 30% and 70%, as well as increases the throughput of long flows by about 1.68x over the state-of-the-art datacenter load balancing schemes.

Biomimetic Recognition-Based Bioorthogonal Host–Guest Pairs for Cell Targeting and Tissue Imaging in Living Animals

Biomimetic Recognition-Based Bioorthogonal Host–Guest Pairs for Cell Targeting and Tissue Imaging in Living Animals

Impact of Temperature on the Immune Interaction between a Parasitoid Wasp and Drosophila Host Species.

Simple SummaryGlobal warming affects most species and their interaction s. Insects are ectotherms, meaning their body temperature is affected by the ambient temperature. This is particularly important for koinobiont parasitoids, insects that keep their host insect alive during development of their eggs and larvae, the host eventually being consumed before adult parasitoids emerge. Temperature changes could therefore affect parasitoids directly and/or indirectly through their impact on the host. Here, we tested the effect of temperature on the parasitic success of two parasitoid lines on two host species, and on each partner independently, to determine whether the host immune response and/or the parasitoid venom proteins, injected with the egg to counteract the host immune response, were affected. The host’s immune defense consists of forming a capsule surrounding the parasitoid egg. In half of the interactions tested, the parasitic success increased with temperature. For one, the increase appeared to result solely from an increased capacity of the parasitoid to escape from a capsule, while for the second, it also appeared to involve a decrease in host encapsulation capacity. Finally, we observed a strong change in venom composition depending on the rearing temperature which may partially explain the change in parasitic success.Temperature is particularly important for ectotherms, including endoparasitoid wasps that develop inside another ectotherm host. In this study, we tested the impact of three temperatures (20 °C, 25 °C and 30 °C) on the host–parasitoid immune interaction using two Drosophila host species (Drosophila melanogaster and D. yakuba) and two parasitoid lines of Leptopilina boulardi. Drosophila’s immune defense against parasitoids consists of the formation of a melanized capsule surrounding the parasitoid egg. To counteract this response, Leptopilina parasitoids rely on the injection of venom during oviposition. Here, we tested the effect of temperature on parasitic success and host encapsulation capacity in response to a parasitoid egg or other foreign body. Increased temperature either promoted or did not affect the parasitic success, depending on the parasitoid–host pairs considered. The mechanisms behind the higher success seemed to vary depending on whether the temperature primarily affected the host immune response or also affected the parasitoid counter-immune response. Next, we tested the effect of parasitoid rearing temperature on its success and venom composition. Venom composition varied strongly with temperature for both parasitoid lines, partially consistent with a change in their parasitic success. Overall, temperature may have a significant impact on the host–parasitoid immune interaction.

Land-use intensity affects the potential for apparent competition within and between habitats.

Arthropod communities dwelling in adjacent habitats are able to impact one another via shared natural enemies. In agricultural landscapes, drastic differences in resource availability between crop and non-crop habitats cause variation in insect herbivore densities over short distances, potentially driving inter-habitat effects. Moreover, the composition of the landscape in which the habitats are embedded likely affects realised attack rates from natural enemies via impacts on local arthropod community structure. Here, we examine indirect effects between herbivore species within and between habitat types by calculating the potential for apparent competition between multiple populations. Firstly, we aim to determine how disparities in resource availability impact the strength of the potential for apparent competition occurring between habitats, secondly to examine the impact of landscape composition upon these effects, and finally to couch these observations in reality by investigating the link between the potential for apparent competition and realised attack rates. We used DNA metabarcoding to characterise host-parasitoid interactions within two habitat types (with divergent nutrient inputs) at 11 locations with variable landscape composition within an agroecosystem context. We then used these interaction networks to estimate the potential for apparent competition between each host pair and to compare expected versus realised attack rates across the system. Shared natural enemies were found to structure host herbivore communities within and across habitat boundaries. The size of this effect was related to the resource availability of habitats, such that the habitat with high nutrient input exerted a stronger effect. The overall potential for apparent competition declined with increasing land-use intensity in the surrounding landscape and exhibited a discernible impact on realised attack rates upon herbivore species. Thus, our results suggest that increasing the proportion of perennial habitat in agroecosystems could increase the prevalence of indirect effects such as apparent competition among insect herbivore communities, potentially leading to enhanced population regulation via increased attack rates from natural enemies like parasitoid wasps.

SpacePHARER: sensitive identification of phages from CRISPR spacers in prokaryotic hosts.

SummarySpacePHARER (CRISPR Spacer Phage–Host Pair Finder) is a sensitive and fast tool for de novo prediction of phage–host relationships via identifying phage genomes that match CRISPR spacers in genomic or metagenomic data. SpacePHARER gains sensitivity by comparing spacers and phages at the protein level, optimizing its scores for matching very short sequences, and combining evidence from multiple matches, while controlling for false positives. We demonstrate SpacePHARER by searching a comprehensive spacer list against all complete phage genomes.Availability and implementationSpacePHARER is available as an open-source (GPLv3), user-friendly command-line software for Linux and macOS: https://github.com/soedinglab/spacepharer.Supplementary information Supplementary data are available at Bioinformatics online.

Bloodmeal sources and feeding behavior of anopheline mosquitoes in Bure district, northwestern Ethiopia

BackgroundMosquito bloodmeal sources determine the feeding rates, adult survival, fecundity, hatching rates, and developmental times. Only the female Anopheles mosquito takes bloodmeals from humans, birds, mammals, and other vertebrates for egg development. Studies of the host preference patterns in blood-feeding anopheline mosquitoes are crucial to determine malaria vectors. However, the human blood index, foraging ratio, and host preference index of anopheline mosquitoes are not known so far in Bure district, Ethiopia.MethodsThe origins of bloodmeals from all freshly fed and a few half-gravid exophagic and endophagic females collected using Centers for Disease Control and Prevention light traps were identified as human and bovine using enzyme-linked immunosorbent assay. The human blood index, forage ratio, and host feeding index were calculated.ResultsA total of 617 specimens belonging to An. arabiensis (n = 209), An. funestus (n = 217), An. coustani (n = 123), An. squamosus (n = 54), and An. cinereus (n = 14) were only analyzed using blood ELISA. Five hundred seventy-five of the specimens were positive for blood antigens of the host bloods. All anopheline mosquitoes assayed for a bloodmeal source had mixed- rather than single-source bloodmeals. The FR for humans was slightly > 1.0 compared to bovines for all Anopheles species. HFI for each pair of vertebrate hosts revealed that humans were the slightly preferred bloodmeal source compared to bovines for all species (except An. squamosus), but there was no marked host selection.ConclusionsAll anopheline mosquitoes assayed for bloodmeal ELISA had mixed feeds, which tends to diminish the density of gametocytes in the mosquito stomach, thereby reducing the chance of fertilization of the female gamete and reducing the chances of a malaria vector becoming infected. Moreover, An. coustani was the only species that had only human bloodmeals, meaning that this species has the potential to transmit the disease. Therefore, combination zooprophylaxis should be reinforced as a means of vector control because the study sites are mixed dwellings.Graphical

Bacteriophages as Therapeutic Agents: Alternatives to Antibiotics.

Bacteriophages are bacterio-specific viruses that constitute the main portion of the environment. Bacteriophages inject their genome into the targeted bacterial cells and some of them can disrupt the metabolism of bacteria and cause bacterial cell disintegration. The application of bacteriophages to kill bacteria is known as bacteriophage therapy. Since bacteriophages target bacteria and are strain-specific, every bacteriophage/bacterial host pair is unique. They are believed to cause no harm to humans. An additional advantage of the strain-specific nature of bacteriophages is that they do not disrupt the beneficial natural flora in the body. Bacteriophage therapy in the West is not a recognized medicine at this time, and no products are registered. Some clinicians are turning to bacteriophage therapy for the treatment of antibiotic-resistant infections. Lack of adverse effects makes bacteriophage therapy ideal for use. Funding research, media attention, and the increased publication of articles helped in a widespread understanding of its therapeutic potential. The first prerequisite for the use of bacteriophage therapy is simply the availability of bacteriophages for treatment, which is often complicated at this stage of bacteriophage production. This includes providing access to all biologically active bacteriophages against the bacterial isolate of the patient and meeting regulatory criteria of purity, traceability, and characterization. A monophage preparation, which is a single bacteriophage, or a phage cocktail, which consists of a number of combined bacteriophages against one or more bacterial species may be used. Accordingly, the antibiotic resistance crisis brought back bacteriophage therapy as a potential complementary or alternative treatment. Bacteriophages are promising cheap antibacterials.

Безопасная реализация виртуальной сети на плоскости данных SDN

The paper continues the investigations on the implementation of virtual networks on the SDN data plane which is modeled by a graph of physical connections between network nodes. A virtual network is defined as a set of ordered host pairs (sender, receiver), and it is implemented by a set of host-host paths that uniquely determine the switch settings. The opportunities to transmit a packet are limited by the host weights (priorities): a packet can be only transmitted from a host to a host if the sender has at most the same priority as the recipient, and thus, a set of paths is permissible if its every subset connects permissible host pairs. In the paper, it is proven that differently from the case when every host pair is permissible, in the graph with priorities a permissible path implementation does not exist for every set of permissible hosts. Moreover, it is shown that is some cases when such an implementation exists, the implementation is not possible without paths with cycles where packets can move infinite and without duplicate paths when a host can get the same packet several times. Using the notion of a perfect set of paths a criterion is established when every permissible set of hosts can be safely implemented by a set of paths without cycles but possibly with duplicate paths.

NCBI's Virus Discovery Codeathon: Building "FIVE" -The Federated Index of Viral Experiments API Index.

Viruses represent important test cases for data federation due to their genome size and the rapid increase in sequence data in publicly available databases. However, some consequences of previously decentralized (unfederated) data are lack of consensus or comparisons between feature annotations. Unifying or displaying alternative annotations should be a priority both for communities with robust entry representation and for nascent communities with burgeoning data sources. To this end, during this three-day continuation of the Virus Hunting Toolkit codeathon series (VHT-2), a new integrated and federated viral index was elaborated. This Federated Index of Viral Experiments (FIVE) integrates pre-existing and novel functional and taxonomy annotations and virus–host pairings. Variability in the context of viral genomic diversity is often overlooked in virus databases. As a proof-of-concept, FIVE was the first attempt to include viral genome variation for HIV, the most well-studied human pathogen, through viral genome diversity graphs. As per the publication of this manuscript, FIVE is the first implementation of a virus-specific federated index of such scope. FIVE is coded in BigQuery for optimal access of large quantities of data and is publicly accessible. Many projects of database or index federation fail to provide easier alternatives to access or query information. To this end, a Python API query system was developed to enhance the accessibility of FIVE.

Identifying likely transmissions in Mycobacterium bovis infected populations of cattle and badgers using the Kolmogorov Forward Equations

Established methods for whole-genome-sequencing (WGS) technology allow for the detection of single-nucleotide polymorphisms (SNPs) in the pathogen genomes sourced from host samples. The information obtained can be used to track the pathogen’s evolution in time and potentially identify ‘who-infected-whom’ with unprecedented accuracy. Successful methods include ‘phylodynamic approaches’ that integrate evolutionary and epidemiological data. However, they are typically computationally intensive, require extensive data, and are best applied when there is a strong molecular clock signal and substantial pathogen diversity. To determine how much transmission information can be inferred when pathogen genetic diversity is low and metadata limited, we propose an analytical approach that combines pathogen WGS data and sampling times from infected hosts. It accounts for ‘between-scale’ processes, in particular within-host pathogen evolution and between-host transmission. We applied this to a well-characterised population with an endemic Mycobacterium bovis (the causative agent of bovine/zoonotic tuberculosis, bTB) infection. Our results show that, even with such limited data and low diversity, the computation of the transmission probability between host pairs can help discriminate between likely and unlikely infection pathways and therefore help to identify potential transmission networks. However, the method can be sensitive to assumptions about within-host evolution.

Biomimetic Recognition and Optical Sensing of Carboxylic Acids in Water by Using a Buried Salt Bridge and the Hydrophobic Effect.

Buried salt bridges widely exist in protein structures but are rarely used in synthetic systems for molecular recognition in water. By mimicking the binding pocket of bioreceptors, we designed and synthesized a pair of endo-functionalized macrocyclic hosts with secondary ammonium groups in a hydrophobic cavity. We found that these macrocycles are able to selectively recognize carboxylic acids in water through salt bridges and the hydrophobic effect. Moreover, it was demonstrated that these macrocyclic receptors can be used in circular-dichroism-based optical chirality sensing of chiral carboxylic acids and fluorescent sensing of phenylpyruvic acid-a biomarker for phenylketonuria. This research showcases that buried salt bridges can be effectively used by endo-functionalized macrocyclic hosts for molecular recognition in water, where solvent screening on polar noncovalent interactions is high.

Long-run bacteria-phage coexistence dynamics under natural habitat conditions in an environmental biotechnology system.

Bacterial viruses are widespread and abundant across natural and engineered habitats. They influence ecosystem functioning through interactions with their hosts. Laboratory studies of phage-host pairs have advanced our understanding of phenotypic and genetic diversification in bacteria and phages. However, the dynamics of phage-host interactions have been seldom recorded in complex natural environments. We conducted an observational metagenomic study of the dynamics of interaction between Gordonia and their phages using a three-year data series of samples collected from a full-scale wastewater treatment plant. The aim was to obtain a comprehensive picture of the coevolution dynamics in naturally evolving populations at relatively high time resolution. Coevolution was followed by monitoring changes over time in the CRISPR loci of Gordonia metagenome-assembled genome, and reciprocal changes in the viral genome. Genome-wide analysis indicated low strain variability of Gordonia, and almost clonal conservation of the trailer end of the CRISPR loci. Incorporation of newer spacers gave rise to multiple coexisting bacterial populations. The host population carrying a shorter CRISPR locus that contain only ancestral spacers, which has not acquired newer spacers against the coexisting phages, accounted for more than half of the total host abundance in the majority of samples. Phages genome co-evolved by introducing directional changes, with no preference for mutations within the protospacer and PAM regions. Metagenomic reconstruction of time-resolved variants of host and viral genomes revealed how the complexity at the population level has important consequences for bacteria-phage coexistence.

Mutual inclinations between giant planets and their debris discs in HD 113337 and HD 38529

ABSTRACT HD 113337 and HD 38529 host pairs of giant planets, a debris disc, and wide M-type stellar companions. We measure the disc orientation with resolved images from Herschel and constrain the three-dimensional orbits of the outer planets with Gaia DR2 and Hipparcos astrometry. Resolved disc modelling leaves degeneracy in the disc orientation, so we derive four separate planet–disc mutual inclination (ΔI) solutions. The most aligned solutions give ΔI = 17°–32° for HD 113337 and ΔI = 21°–45○ for HD 38529 (both 1σ). In both systems, there is a small probability (<0.3 per cent) that the planet and disc are nearly aligned (ΔI < 3○). The stellar and planetary companions cause the orbits of disc material to precess about a plane defined by the forced inclination. We determine this as well as the precession time-scale to interpret the mutual inclination results. We find that the debris discs in both systems could be warped via joint influences of the outer planet and stellar companion, potentially explaining the observed misalignments. However, this requires HD 113337 to be old (0.8–1.7 Gyr), whereas if young (14–21 Myr), the observed misalignment in HD 113337 could be inherited from the protoplanetary disc phase. For both systems, the inclination of the stellar spin axis is consistent with the disc and outer planet inclinations, which instead supports system-wide alignment or near alignment. High-resolution observations of the discs and improved constraints on the planetary orbits would provide firmer conclusions about the (mis)alignment status.

Avoiding bottlenecks in networks by short paths

Data center networks are typically characterized by high density communication components that process and exchange large amount of information using shortest paths. Mostly, data centers network topologies contain multi-rooted tree with multiple equal cost shortest paths between pairs of hosts. Usually, data center networks operation is based on the result of shortest path algorithms and per-flow static hashing which may cause poor network utilization rates with some links becoming congested while some parts of the network are underused. This work presents a flow scheduling algorithm that exploits the path diversity in data center topologies and dynamically reroutes large flows through less congested shortest and non-shortest paths based on the current state of the network without causing packets reordering. The algorithm aims to minimize flows latency while maximizing the network utilization rates. Results show that the algorithm proposed in this work reduces flows completion time by 13–24% over Equal-Cost Multi-Path routing, while improving the average network utilization by up to 10%.

Shining Light on Human Gut Bacteriophages.

The human gut is a complex environment that contains a multitude of microorganisms that are collectively termed the microbiome. Multiple factors have a role to play in driving the composition of human gut bacterial communities either toward homeostasis or the instability that is associated with many disease states. One of the most important forces are likely to be bacteriophages, bacteria-infecting viruses that constitute by far the largest portion of the human gut virome. Despite this, bacteriophages (phages) are the one of the least studied residents of the gut. This is largely due to the challenges associated with studying these difficult to culture entities. Modern high throughput sequencing technologies have played an important role in improving our understanding of the human gut phageome but much of the generated sequencing data remains uncharacterised. Overcoming this requires database-independent bioinformatic pipelines and even those phages that are successfully characterized only provide limited insight into their associated biological properties, and thus most viral sequences have been characterized as “viral dark matter.” Fundamental to understanding the role of phages in shaping the human gut microbiome, and in turn perhaps influencing human health, is how they interact with their bacterial hosts. An essential aspect is the isolation of novel phage-bacteria host pairs by direct isolation through various screening methods, which can transform in silico phages into a biological reality. However, this is also beset with multiple challenges including culturing difficulties and the use of traditional methods, such as plaquing, which may bias which phage-host pairs that can be successfully isolated. Phage-bacteria interactions may be influenced by many aspects of complex human gut biology which can be difficult to reproduce under laboratory conditions. Here we discuss some of the main findings associated with the human gut phageome to date including composition, our understanding of phage-host interactions, particularly the observed persistence of virulent phages and their hosts, as well as factors that may influence these highly intricate relationships. We also discuss current methodologies and bottlenecks hindering progression in this field and identify potential steps that may be useful in overcoming these hurdles.

Kinetic Fingerprinting Links Bacteria-Phage Interactions with Emergent Dynamics: Rapid Depletion of Klebsiella pneumoniae Indicates Phage Synergy.

The specific temporal evolution of bacterial and phage population sizes, in particular bacterial depletion and the emergence of a resistant bacterial population, can be seen as a kinetic fingerprint that depends on the manifold interactions of the specific phage–host pair during the course of infection. We have elaborated such a kinetic fingerprint for a human urinary tract Klebsiella pneumoniae isolate and its phage vB_KpnP_Lessing by a modeling approach based on data from in vitro co-culture. We found a faster depletion of the initially sensitive bacterial population than expected from simple mass action kinetics. A possible explanation for the rapid decline of the bacterial population is a synergistic interaction of phages which can be a favorable feature for phage therapies. In addition to this interaction characteristic, analysis of the kinetic fingerprint of this bacteria and phage combination revealed several relevant aspects of their population dynamics: A reduction of the bacterial concentration can be achieved only at high multiplicity of infection whereas bacterial extinction is hardly accomplished. Furthermore the binding affinity of the phage to bacteria is identified as one of the most crucial parameters for the reduction of the bacterial population size. Thus, kinetic fingerprinting can be used to infer phage–host interactions and to explore emergent dynamics which facilitates a rational design of phage therapies.