The interest in using polymer-dispersed reinforcement in the construction industry in the context of sustainability has led to significant research on this scientific problem. The article is devoted to studying the processes of fiber interaction depending on its dispersion and the concrete matrix, and their combined contact work during the formation of a concrete structure, work under stresses arising in a concrete body, and during a collapse. The physical and mechanical processes of deformation and destruction of the “matrix–fiber” system were studied using high-precision microscopic equipment, and the nature of the work and deformation of fibers in concrete were revealed. The work aimed to establish and characterize the quantitative and qualitative aspects of the concrete matrix and dispersion-reinforcing fiber combined work. It was established that the best values of the adhesion index were observed at a volume content of fiber in the amount of 2% by weight of cement, regardless of the type of dispersion-reinforcing fiber. It was shown that the microstructure of polydispersion-reinforced fiber-cement specimens was denser, and microcracks formed during fracture in polydispersion-reinforced specimens had a smaller opening width. It was established that polydispersion-reinforced concrete had higher values of strength (up to 126%) and deformation (up to 296%) characteristics compared to monodispersion fiber-reinforced concrete. Current trends in the development of architectural, planning, and design solutions for building and structure technologies for the construction of objects for various purposes require radical improvements in the physical, mechanical, and operational characteristics of products and structures, reducing material, labor, and energy recourses. In this regard, the theoretical substantiation and development of new effective materials based on polymers, their testing methods, calculation, and design of structures are relevant and of scientific interest. One of the most promising among modern building materials is fiber-reinforced concrete, which contributes to the solution of this problem. At the same time, the scope of the practical application of this composite material can be significantly increased in the case of obtaining more detailed and reliable information about its various and unique properties and characteristics. A severe disadvantage of concrete is fragility in fracture, which occurs as a result of the almost instantaneous propagation of the main crack after slight plastic deformation. However, in the case of ideally brittle fractures, it is possible to reconstruct a sample of the same sizes from parts obtained during testing without gaps between them. A brittle fracture most often occurs along certain crystallographic planes inside grains. This so-called intragranular fracture can be realized by cleavage and shearing, which differ in the type of fracture surfaces ,2,3,4,5.As studies ,7,8,9 of-Obtaining a composite with greater strength than with monodispersed reinforcement;-Purposeful regulation of the complex of physical and mechanical properties of the composite over a broader range than with monodispersed reinforcement;-The possibility of improving the indicators of durability and operational characteristics of the composite ,19,20,21The degree of all these changes in material properties and the structures’ characteristics is mainly determined by the type and properties of the fibers and concrete used and the degree of interaction between them. Thus, a close relationship of reinforcing fibers with a concrete matrix, in addition to its activity, is provided by the length of the boundaries, which depends on the degree of saturation of concrete with fibers, their geometric characteristics, and surface energy ,11,12,13Dispersion-reinforcing fibers have also found wide application in cellular concrete technology ,27,28,29The conducted literature review, firstly, showed that the actual direction of building science is the study of fiber reinforcement of concrete. At the same time, all the work carried out in this direction is quite relevant due to the universality of the concept of “fiber-reinforced concrete” and the expanded number of technological and recipe possibilities for controlling the properties of various concretes due to numerous combinations and techniques associated with dispersed reinforcement. Furthermore, it should be noted that many studies are closely related to each other due to the fact that the influence of various parameters of dispersed reinforcement should often be considered in a synergistic sense. For example, this can be a simultaneous study of the influence on the properties of fiber-reinforced concrete of both dispersion parameters, that is, the geometry and quantitative aspect of the fibers, and its structural aspect, that is, the percentage of reinforcement, and, finally, from the point of view of the qualitative composition, that is, the material from which the dispersion-reinforcing fibers are made. In this regard, certain scientific deficits require additional research in terms of quantitative and qualitative aspects, and this requires high-precision, microscopic, and other analytical equipment, as well as certain methodological tools to establish specific, measurable characteristics of work, both qualitative and quantitative, in the joint interaction of the matrix of cement stone and concrete as a whole with dispersion-reinforcing fibers filling the concrete structure. In addition, the literature review showed that data on the effect of polydispersed reinforcement on the strength of fiber-reinforced concrete is much less than that of monodispersed reinforcement. However, these data are sufficient to conclude that it is possible to ensure regulation of material properties within broader limits than with monodispersed reinforcement ,31,32,33From the point of view of fundamental science, the question of the joint work of concrete and fiber dispersion-reinforcing fiber remains completely unexplored at present. The processes occurring at the interface between the cement stone, aggregate, if any, and fiber have not been studied; the issue of fiber deformation is of interest. If the destruction and rupture of fibers have been studied to a more or less certain extent, then the deformations of fiber, which are at the micro-level a reinforcing rod with a high degree of flexibility, have not been studied in detail. Therefore, it is essential to obtain fundamental knowledge about the processes of interaction of fiber and a concrete matrix, their joint work in terms of contact, during the formation of a concrete structure, during operation, under stresses arising in the concrete body, and destruction, which is most interesting and is an unexplored physical–mechanical process, which can be investigated only by using high-precision microscopic equipment. The motivation for the study was the reasonable relevance of a new generation of fiber-reinforced concrete due to the increased requirements for construction objects and building materials. The study aimed to determine the qualitative and quantitative aspects of concrete and fiber combined work with monodispersed and polydispersed reinforcement. At the same time, the achievement of the goal was methodologically planned as the implementation of a new approach to research based on the formula, technological and microstructural aspects, and consideration of the synergistic system of the composite material “cement matrix–concrete matrix–fiber”. Thus, the tasks of the study include microscopic analysis of the contact zone and the nature of deformation and destruction of fiber and a concrete matrix during the destruction of fiber-reinforced concrete composites, identifying the possibility of a qualitative and quantitative assessment of such interaction, and then conducting a quantitative assessment of this work and a qualitative analysis with the characterization and construction of a picture of the physical and mechanical processes occurring during the operation of fiber-reinforced concrete elements.To begin to determine the order of the program and the plan of experimental and analytical studies, one should determine the methodological apparatus of the study and consider in-depth the main aspects that are touched upon in this study.Thus, from the point of view of methodology, as it was already established above in the literature review and analysis of the current state of the problem, there is a shortage of complex synergistic methods that simultaneously consider several aspects of the work of concrete and fiber. Thus, the methodological aspect consists, firstly, in considering fiber-reinforced concrete as a composite system consisting of a matrix of cement stone, which is part of another composite material—concrete, where it also acts as a matrix where the fillers in concrete are aggregates and fibers. In this case, the fiber is considered in direct interaction with the cement stone, with a matrix consisting exclusively of hardened, prohydrated cement. This approach is due to the possibility of additional microscopic examinations from the point of view of studying the behavior of fiber dispersion reinforcing fibers during operation under load and considering fibers as dispersed reinforcement at the micro-level. The research methodology from the point of view of the formulation is to select, based on the available literature data, the initial components of fiber-reinforced concrete in order to direct the study in a specific measurable direction, namely, the study of the behavior of fibers under load in concrete. The most rational raw material components  were those components that are listed below.From the point of view of technology, the sequence of introducing the components was determined, the order of their mixing was determined, and the subsequent homogenization was carried out in accordance with the previously-developed most effective proposals of the authors indicated in the “Introduction”.From the point of view of the study, a methodology was developed that consists of the manufacture and proper curing of prototypes of cement stone reinforced with dispersion fiber, intended for microstructural studies and their analysis, and coarse concrete, intended for understanding the quantitative characteristics of work—improved concrete in general.During the research, we used Portland cement, grade PC 500 D0  , withoutGranite crushed stone  was used as a large dense aggregate, the physical and mechanical characteristics of which are presented in Glass fiber   pretreatFiber types A and B differed in geometric parameters and both were treated with surfactants.To develop combinations of polydispersed reinforcement and predict their effectiveness, it seems appropriate to determine the amount of adhesion of glass fiber to the matrix.Most often, the destruction of fiber-reinforced concrete occurs due to the pulling of fibers from the concrete as a result of a breakdown of the bond at the fiber–matrix interface. Thus, by increasing the adhesion strength of the fiber to the matrix, it is possible to maximize the use of strength properties of fiber, up to its rupture at the moment of destruction of the composite. The adhesion of the fiber to the concrete matrix of the composite is the result of the combined action of adhesion, friction, and mechanical engagement in the zone of their contact with the cement stone. The influence of each of these factors on the anchoring of fibers in the matrix can be different and depends on the composition, structure, and properties of the cement stone and the fibers’ material, shape, and size. Thus, the main mechanism for increasing the strength of dispersion-reinforced concrete is an increase in the adhesion strength of the reinforcing fiber with the concrete matrix of the composite .Determination of the adhesion index of the fiber to the matrix consists of finding experimentally such a minimum percentage of concrete reinforcement, up to which the introduced fibers practically do not show a reinforcing effect, but after which a steady increase in the strength of the composite is observed . Table 4l and d are the length and diameter, respectively, of the fiber [As a starting mixture, a cement paste of normal density is used. Then, reinforced and unreinforced samples of a certain composition are prepared from one batch, and according to the test results, a graph “Strength–volumetric content of fiber” is plotted. As for the adhesion characteristics of fibers with a cement stone from a dough of normal density , they arτ=Rfc−3.5The experimental research program is presented in One series of samples includes three beams with dimensions of 40 × 40 × 160 mm. Each series of specimens was tested for compression and flexural tension.Based on the results of preliminary experimental studies, the most effective type of dispersed reinforcement and the reinforcement coefficient were determined.The main experimental part included the manufacture of concrete and fiber-reinforced concrete samples to determine the following characteristics: cube compressive strength ; prismatic compressive strength and ultimate deformations during axial compression ; tensile strength in bending ; and axial tensile strength and ultimate deformations during axial tension .The preparation of the fiber-reinforced concrete mixture was carried out in a BL–10 laboratory forced-action concrete mixer with the following sequence of loading the components: fine aggregate, Portland cement, and water. Upon reaching the homogenization of the mixture of the binder, grout, and fine aggregate, fiber was introduced into it. Mixing of the fiber cement–sand mixture was carried out for 3 min until the fiber was thoroughly distributed in the volume of the mixture, after which coarse aggregate was introduced into it. To compact the mixtures in the process of forming the samples, a standard vibrating platform was used, and the vibration time was 90 s. On the next day after molding, the samples were stripped and placed in a normal hardening chamber for 28 days until the design strength was achieved.Compressive and tensile flexural strength tests were carried out in accordance with GOST 10180-2012 “Concretes. Methods for strength determination using reference specimens”  ; an SMZh-539-220A laboratory vibrating platform ; hydraulic press IP–1000 ; an R-50 tensile testing machine ; a 500 mm metal measuring ruler, laboratory scales, an NPL-1 device for measuring deviations from the plane, and an NPR-1 device for measuring deviations from perpendicularity  ,39,40,41The study of the microstructure of polydispersion-reinforced and monodispersion-reinforced fiber cement samples was carried out by scanning electron microscopy (SEM).The study of the microstructure of a dispersion-reinforced cement stone to determine the size of microcracks, the shape of structural elements, and their orientation in space was carried out using a ZEISS CrossBeam 340 double-beam scanning electron/ion microscope equipped with an Oxford Instruments X-Max 80 X-ray microanalyzer (Carl Zeiss Microscopy GmbH (Factory), Jena, Germany).The results obtained from preliminary tests of prototypes of fiber cement beams are presented in As for the polydispersion-reinforced fiber-cement specimens, their compressive strength values were higher compared to the strength of monodispersion-reinforced specimens. For example, the compressive strength values for compositions of the 3AB, 6AB, 9AB, and 12AB types were 56.4 MPa, 62.7 MPa, 65.7 MPa, and 63.7 MPa, respectively.It should also be noted that the effects of the volumetric content of fiber in the composition of the cement matrix, both in the case of monodispersed reinforcement with type A fibers and monodispersed reinforcement with type B fibers, were similar, namely, with an increase in the percentage of reinforcement from 1 to 4%, an increase in strength was observed. In the case of polydispersed reinforcement, with the introduction of type A and B fibers with ratios of 0.5 and 0.5% and 1 and 1%, an increase in strength characteristics was observed; with the introduction of these fibers in a ratio of 1.5% and 1.5%, the maximum strength value was recorded; and with the introduction of these fibers in the amount of 2 and 2%, a decrease in strength was observed.From Let us consider the nature of the change in the tensile strength in bending of fiber cement specimens reinforced with glass fiber in the range from 0 to 4% . DependeFrom Point B corresponds to the situation when from the moment cracks appeared in the cement matrix, the applied load was absorbed by the fiber and provided the bearing capacity.The BC section defines the so-called “concentrated reinforcement zone”, and point C is the moment of merging of the contact zones that arose in the process of structure formation near the “fiber–matrix” interface, and thus the formation of a bulk fiber cement framework.Section CD characterizes a further, and more intensive, increase in strength in the “zone of carcass reinforcement”, which is the result of the consolidation of the cement stone between the fibers. Point D corresponds to the achievement of the maximum strength, after which its decrease was observed, caused by a decrease in the thickness of the matrix layer so that the material tended to delaminate.The strength of polydispersion-reinforced specimens changed in a similar way .An analysis of literary sources made it possible to establish that most often, the volume content of glass fibers in fiber-reinforced concrete is 1.5–3.0% ,31,32,33Thus, according to the results of preliminary experimental studies, the indicator of adhesion of glass fiber to a cement stone for monodispersion-reinforced samples was calculated .Analyzing the calculated values of the adhesion index of the fiber to the cement stone, it can be seen that the values of the adhesion to the cement matrix for the compositions of type A were higher than those for the compositions of type B. In both cases, the best values of the adhesion index were observed with a fiber volume content of 2% by weight of cement.Photographs of the microstructure of polydispersion-reinforced and monodispersion-reinforced fiber cement samples are shown in Analyzing the photographs of the microstructures of the dispersion-reinforced fiber-cement samples presented in As an analysis of the photographs of the microstructure in Thus, it can be concluded that with polydispersed reinforcement, we first of all strengthened the “cement matrix–fiber” contact zone, and with monodispersed reinforcement, this zone was not reinforced, pulling out occurred at lower loads, the fiber was less resistant to pulling out, and thus the overall effect of the use of fiber dispersion-reinforcing fiber was diminished.Heavy concrete of class B30 with the required workability grade P1 (cone draft of 1–4 cm) was designed as a control composition for the manufacture of test concrete samples. The content of coarse aggregate fractions is represented by the following ratio: 60%—fraction 10–20 mm; 40%—fraction 5–10 mm. The parameters of the composition of the concrete mixture obtained as a result of calculations are shown in Polydispersion-reinforced fiber-reinforced concrete samples were made from a similar composition of a concrete mixture with the addition of a combination of glass dispersion-reinforcing fibers in the amount of 3% of the cement mass, where one half was represented by fibers with a length of 6 mm and a diameter of 9 microns, and the other half was represented by fibers with a length of 12 mm and a diameter of 13 microns. The test results of concrete and fiber-reinforced concrete (FRC) samples of the main experimental part are presented in After analyzing the data presented in Thus, the increase in cube compressive strength in polydispersion-reinforced fiber-reinforced concrete specimens in comparison with specimens from heavy concrete was 10%, the increase in prismatic compressive strength was 11%, tensile strength in bending increased by 126%, axial tensile strength increased by 45%, ultimate deformations under axial compression increased by 37%, ultimate deformations under axial tension increased by 296%, and the value of the elastic modulus increased by 12%.Analysis of cracking and destruction showed a significant difference in the behavior of unreinforced and dispersion-reinforced concrete .Unreinforced concrete collapsed with the formation of the first signs of cracking on the lateral faces of the specimen shortly before destruction, which occurred with the formation of a main vertical crack with minimal branching.Polydispersion-reinforced concrete collapsed with the formation of multiple cracks with their characteristic branching, which indicates its high viscosity, as well as a higher energy consumption of the destruction process, which, in general, predetermines the high impact endurance of fiber-reinforced concrete in relation to the original unreinforced concrete.In addition, according to the test results, compression diagrams As can be seen from Analyzing changes in deformation diagrams for various types of studied compositions, one can note the practical applicability of the data obtained. Taking into account the change in deformability and giving the material a more viscous character of destruction, creating a damping effect, we had the opportunity to control the properties by changing the qualitative and quantitative structures of concrete. Using fiber reinforcement, we achieved greater operational versatility of the produced concrete and expanded practical applicability in flexible construction requiring new approaches.f > lcr.fl), then most of them will break at the moment of failure of the composite, and the fracture toughness will be low, and if (f < lcr.fl), then the main contribution to the resistance of the composite to destruction will be made by the energy expended on pulling the fibers from the matrix.In general, the fracture toughness of the composite depends on the type and properties of the initial components and the volume ratio between them, mainly on the degree of saturation of the matrix with reinforcing fibers, and is ultimately determined by the strength of the phase boundaries. In this case, if the length of the fibers is greater than a certain critical length  .During the manufacture and molding of experimental fiber-reinforced concrete samples, the greatest segregation of the fiber-reinforced concrete mixture was observed in monodispersion-reinforced fiber-reinforced concrete, made using glass fiber with dimensions d = 9 μm and l = 6 mm, and the smallest in polydispersion-reinforced fiber-reinforced concrete. At the same time, the workability of the mixture was maintained constant . To reduce or eliminate the segregation of the fiber-reinforced concrete mixture when using this method for field application, the use of plasticizing additives is recommended.Analysis of the results obtained in the study in the course of comparison with the results obtained earlier by other authors ,30,31,32A new methodological approach is proposed that considers the “dispersion fiber–cement matrix” system as a microsystem, similar to the “reinforcing rod–concrete matrix” macrosystem. The obtained fundamental new knowledge about the processes occurring during the operation of dispersion fiber in reinforced concrete is presented, which consists of studying the processes of destruction and deformation of fiber, based on computational studies, numerical studies, and microscopic analyses.-Monodispersion-reinforced fiber-cement specimens made using type B fibers have higher values of compressive strength (up to 12%) and tensile strength in bending (up to 70%) in comparison with fiber-cement specimens reinforced with type A fibers;-The best values of the adhesion index are observed with the volumetric fiber content in the amount of 2% of the cement mass, regardless of the type of dispersion-reinforcing fiber;-The microstructure of polydispersion-reinforced fiber-cement specimens is denser, and microcracks formed in the process of destruction of specimens have a smaller opening width (from 60 to 130%) in polydispersion-reinforced specimens;-Polydispersion-reinforced concretes have higher values of strength (up to 126%) and deformation (up to 296%) characteristics in comparison with monodispersion-reinforced fiber-reinforced concrete.Analysis of literature data, as well as data obtained during our own experiments, allows us to formulate the following main conclusions:Thus, the main goal of the study was achieved; the main qualitative and quantitative aspects of the joint work of concrete and fiber with monodispersed and polydispersed reinforcement were determined and their results were evaluated, which are proposed to be used in the technology of new highly functional concrete with improved strength and deformation characteristics, designed to gradually displace traditional reinforced concrete.Prospects for further research based on the results of the analysis are seen in the study of new theoretical and practical dependencies that arise during the formation of the structure, the establishment of properties, and the change in the nature of the work of various fiber-reinforced concretes under various types of stress–strain states, made from various components and operated in various conditions, for even greater universalization of the proposed concept and methodology.


The results showed that, compared with the 0.25% Met group, the final body weight (FBW), average daily gain (ADG), EP, egg weight (EW), and average daily feed intake (ADFI) in the other groups were significantly increased and feed egg ratio (FER) was decreased. Meanwhile, the EW and yield of abdominal fat (AFY) in the 0.47% Met group were higher than those in other groups. The triglyceride (TG), estradiol (E2), total protein (TP), albumin (ALB), and immunoglobulin A (IgA) in the 0.38 and 0.47% Met groups were higher than those in other groups. In addition, 16S rRNA gene sequencing revealed that there was no difference in the Sobs index, ACE index, and Shannon index among all groups. However, it is worth noting that feeding low protein diets with Met changed the gut microbial composition . Also, our results showed that the changes in gut microbial composition induced by the diets with different levels of Met were closely related to the changes of key parameters: ADFI, EW, FBW, TG, EM, EP, ADG, FER, and uric acid (UA). Our results highlight the role of adding an appropriate amount of Met to the low protein diet in laying hens, which could improve the gut microbial composition, production performance, reproductive system, and nutrient metabolism of laying hens. In conclusion, this study suggested that when the Met level was 0.38%, the production performance of the laying hens was pretty good.This study investigated the effects of different levels of methionine (Met) in a low protein diet on the production performance, reproductive system, metabolism, and gut microbial composition of laying hens to reveal the underlying molecular mechanism of Met in a low protein diet on the host metabolism and gut microbial composition and function of hens. A total of 360 healthy 38-week-old Peking Pink laying hens with similar body conditions and egg production (EP) were randomly divided into four groups with nine replicates per treatment and 10 hens per replicate. The hens in each treatment group were fed low protein diets containing different levels of Met  for 12 weeks. Feed and water were provided  The poultry industry shows a trend of large-scale, intelligent, and standardized development, and the demand for protein feed resources continues to increase , 2. HoweBifidobacterium and Lactobacillus, maintain the integrity of the intestinal epithelial barrier function, improve the normal functions of the intestinal epithelium, and enhance intestinal mucosal immunity in animals (That refers to the low protein diet that containing less crude protein than the nutrient requirements of poultry (NRC) recommends for feeding in the diet. Following the ideal amino acid pattern is the key to feed formulation design. In essence, the need for protein in the diet is the need for amino acids, which are essential nutrients for animal growth and development that are involved in important biochemical reactions in animals , 13. The animals –23.In order to avoid the negative effects of a low protein diet on livestock and poultry, we can consider adding essential amino acids to their diet to reduce harmful effects . MethionDue to the current situation, low protein diets will be a trend in the future. However, the application of a low crude protein diet in laying hens is relatively rare at present, and the study on its functional effect on laying hens can better prepare balanced low protein diets, which is conducive to exerting the genetic potential of laying hens. To develop a practical understanding of Met use in low crude protein diets, a study was conducted to evaluate production performance, egg quality, reproductive system, host metabolism, and the gut microbial composition responses to different levels of Met in laying hens fed low protein diets.All experiments were approved by the China Agricultural University Animal Care and Use Committee .ad libitum during the entire experimental period. At the same time, to ensure that the chicken coop is closed and ventilated, the average relative humidity was routinely maintained at ~55%, and it was ensured that the hens get 16 h of light every day. In order to meet the nutritional requirements of the laying hens (NYT33-2004), a basal corn-soybean meal diet was formulated. A pre-experiment was conducted for one week before the start of the formal experiment to ensure that the animals were acclimated to the new experimental environment and diet, meanwhile, it could empty the original intestinal contents, and estimate the approximate feed intake of the experimental animals. The four experimental groups were fed with low protein diets containing 0.25, 0.31, 0.38, and 0.47% Met , respectively. The ingredients and nutrient composition of the diets are shown in A total of 360 commercial hens of the Peking Pink strain  at the age of 38 weeks with similar egg production and healthy bodies were randomly divided into four treatment groups with nine replicates per group and 10 birds per replicate. The hens were placed in five cages (two birds in each cage) and each cage (H45 cm × W45 cm × D45 cm) was equipped with a nipple drinker and an exterior feed through to ensure feed and water were provided Table 2.The difference between the full bucket weights and the remaining feed was calculated as the weekly feed intake, and the body weights of the laying hens were recorded every week at the same time to calculate the average daily feed intake (ADFI) and feed egg ratio (FER). The number of eggs and egg weight were accurately recorded every day to calculate the average daily egg mass (EM), egg weight (EW), and egg production (EP) rate. The hens were weighed in replicates at the beginning and end of the experiment to calculate average daily gain (ADG). After the beginning of the experiment, 30 eggs were randomly selected from each treatment group every 4 weeks to measure egg quality parameters as shown in The eggshell strength was measured by the egg force reader (ESTG-01COrka Teachnology Ltd); The eggshell thickness was measured using the eggshell thickness tester ; Haugh unit, yolks color, and egg weight were measured by multifunctional egg quality tester . The eggshell color was measured by QCR color reflectometer . Weigh the eggshell, then separate the yolk with a separator, and then weigh the ratio of yolk and the ratio of albumen.At the end of the experiment, blood samples were collected from the wing veins of the laying hens on the same day of sampling and centrifuged at 3,000 rpm for 15 min at room temperature to separate the serum. After that, the serum samples were collected by a pipette into 1.5-ml tubes and stored at −20°C. Triglyceride (TG), uric acid (UA), urea, total protein (TP), albumin (ALB), and immunoglobulin M (IgM) in serum were determined using an automatic biochemical analyzer  according to the manufacturer's instructions. Superoxide dismutase (SOD) and glutathione (GSH) in the serum were determined using a commercial kit  according to the kit instructions.Seventy hens were euthanized and weighed by a sodium pentobarbital injection . Abdominal adipose tissue was weighed to calculate the yield of abdominal fat (AFY). The liver, kidneys, fallopian tubes, and ovaries were removed, weighed, and the number of follicles was recorded to calculate the liver index, fallopian tube index, and ovary index.The cecal contents of laying hens were collected, immediately frozen in liquid nitrogen, and stored at −80°C. Cecal microbial DNA was isolated with an Omega Bio-tek stool DNA kit  and quantified by a NanoDrop 2000 spectrophotometer . Then, the V3–V4 region of the 16S rRNA gene was amplified with 338F and 806R primers with the sequence of 5′-ACTCCTACGGGAGCAGCA-3′ and 5′-GGACTACHVGGGTWTCTAAT-3′. Afterward, DNA samples were quantified, followed by the amplification of V3V4 hypervariable region of the 16S rDNA. Final amplicon pool was evaluated by the AxyPrep DNA gel extraction kit . Paired-end reads were generated with an Illumina MiSeq PE250 , and the reads were filtered out with default parameters.p < 0.05. Data were expressed as the mean ± SE.All results were subjected to a one-way ANOVA procedure and differences were examined using Duncan's multiple range test to evaluate the differences within treatments using SPSS version 18.0 . The trends of the linear and quadratic analyses were conducted using SAS software version 8.0 . Differences were considered significant at The raw paired-end reads were assembled into longer sequences, and quality was filtered by PANDAseq (version 2.9) to remove the low-quality reads. The high-quality sequences were clustered into operational taxonomic units (OTUs) with a 97% similarity using UPARSE (version 7.0) in QIIME (version 1.17) , 33, andp < 0.001). On the contrary, the FER in the 0.25% Met group was significantly higher than the other three groups (p < 0.001), while there was no significant difference among the other three groups. The AFY in the 0.47 and 0.38% Met groups was significantly higher than that in the 0.25% Met group (p < 0.01). The EW in the 0.38% Met group was significantly lower than that in the 0.47% Met group (p < 0.001), the liver index was lower than that in the 0.25% Met group (p < 0.05), and IBW was not significantly affected by different dietary Met levels  was obtained. When the Met level was increased to 0.41%, the maximum EM (54.32 g/d) and minimum FER (2.04) were obtained, and the Met intake was 0.45, 0.46, and 0.46 g/d, respectively . When thp < 0.001). The EW at 46 weeks of age in the 0.25% Met group was lower than that in the 0.31 and 0.47% Met groups (p < 0.05). The eggshell proportion at 46 weeks of age in the 0.25% Met group was higher than that in the 0.31% Met group (p < 0.05). The albumen ratio at 42 weeks of age in the 0.25% Met group was lower than that in the 0.31% Met group (p < 0.05), while the albumen ratio at 50 weeks of age was lower than that in the 0.47% Met group (p < 0.05). On the contrary, the yolk ratio at 42 weeks of age in the 0.25% Met group was higher than that in the 0.31% Met group (p < 0.05). The eggshell thickness in the 0.38% Met group at 46 weeks of age was significantly higher than that in the other three groups (p < 0.01), and there was no significant difference among the other three groups. The yolk color value in the 0.31% Met group at 50 weeks of age was the lowest and lower than that of the 0.25% Met group (p < 0.05). However, other indicators such as eggshell color, eggshell strength, and Haugh unit were not significantly affected by the different levels of dietary Met (As shown in tary Met .p < 0.01). Furthermore, IgA was higher than that in the 0.31% Met group (p < 0.05), while the TG, ALB, and E2 in the 0.38% Met group were significantly higher than those in the 0.31% Met group (p < 0.01). The TG in the 0.25% Met group was significantly lower than that in the 0.38 and 0.47% Met groups (p < 0.001), and UA was higher than that in the 0.31 and 0.47% Met groups (p < 0.05). However, other biochemical indices were not significantly affected by different dietary Met levels   in the serum of laying hens. In particular, the TG and E2 in the 0.47% Met group were significantly higher than those in the 0.31% Met group (and IgM) .p < 0.01) but it had no significant effects on oviduct length, ovary weight, and ovary weight after the removal of dominant follicles, etc., . On the contrary, Faecalitalea was negatively correlated with these traits (p < 0.05), while it was positively correlated with FER, but not significantly. Elusimicrobium was positively correlated with ADFI, EW, FBW, EM, EP, and ADG but negatively correlated with FER (p < 0.05). Norank_f_Christensenellaceae was significantly positively correlated with ADFI, EW, TG, EM, and ADG, but negatively correlated with FER and UA (p < 0.05). Norank_P_Saccharibacteria was significantly positively correlated with EW, ADFI, FBW, and TG (p < 0.05). [Eubacterium]_coprostanoligenes_group was significantly positively correlated with EW (p < 0.05). In contrast, Faecalicoccus was significantly negatively correlated with ADFI, FBW, TG, EM, EP, and ADG (p < 0.01), but positively correlated with FER (p < 0.05). Family_xii_ad3011_group was negatively correlated with ADFI, but positively correlated with UA (p < 0.05). [Eubacterium]_Brachy_group was negatively correlated with ADFI, FBW, EM, EP, and ADG (p < 0.05). Coprococcus_1 was negatively correlated with EW and TG (p < 0.05). [Clostridium]_innocuum_group was significantly negatively correlated with FBW and TG (p < 0.05). There was a certain correlation between the production traits and other unmentioned intestinal microflora of laying hens, but their influence is not significant  can be found at: The animal study was reviewed and approved by China Agricultural University Animal Care and Use Committee .MM, QM, JZ, and SG designed the study. MM, SG, and SH conducted the experiments, drafted the manuscript, polished the manuscript, and finished the submission. MM, ML, and SG guided the analysis of the experimental data. QM, LZ, and JZ helped with revisiting and reviewing the manuscript. All authors read and approved the final manuscript.This study was supported by the National Science Foundation of China (Grant No. 31772621), a Special Fund for China Agricultural Research System program (CARS-40-K08), National Key Research and Development Program of China (2017YFD0500500), and the Special Fund from Chinese Universities Scientific Fund (2018TC043).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Escherichia coli, identifying 90 synergistic interactions. Identified gene targets were subsequently tested for antibiotic synergy on the transcriptomic level via multiplexed CRISPR-dCas9 and showed successful sensitization of E. coli without a separate fitness cost. These fitness neutral gene perturbations worked as co-therapies in reducing a Salmonella enterica intracellular infection in HeLa. Finally, these results informed the design of four antisense peptide nucleic acid (PNA) co-therapies, csgD, fnr, recA and acrA, against four MDR, clinically isolated bacteria. PNA combined with sub-minimal inhibitory concentrations of trimethoprim against two isolates of Klebsiella pneumoniae and E. coli showed three cases of re-sensitization with minimal fitness impacts. Our results highlight a promising approach for extending the utility of current antibiotics.Proliferation of multidrug-resistant (MDR) bacteria poses a threat to human health, requiring new strategies. Here we propose using fitness neutral gene expression perturbations to potentiate antibiotics. We systematically explored 270 gene knockout-antibiotic combinations in  Escherichia coli. These neutral fitness interactions worked as co-therapies in a Salmonella enterica infection and informed the design of re-sensitization therapies in multi-drug resistant E. coli and Klebisiella pneumoniae clinical isolates.Otoupal et al. use a systematic approach to investigate the effects of fitness neutral gene perturbations and antibiotic synergy in  Both the World Economic Forum3 and the World Health Organization4 warn of calamitous economic and health outcomes if current trends continue unabated; while approximately 1 million people die from such infectious yearly, annual deaths attributable to antibiotic resistant infections are estimated to reach 10 million by 20505. This problem is likely to be exacerbated as multidrug-resistant (MDR) bacteria continue to emerge, necessitating the pursuit of alternative antimicrobial strategies.Antibiotic resistance is one of the foremost problems facing humanity. Estimates for the yearly cost imposed by antibiotic resistance reaches as high as $55 billion in the United States7. In this model, while scientists continue to discover and bring to market novel drugs, it is almost universally accepted that bacteria will continue to evolve resistance and thus inexorably diminish a therapy’s efficacy over time8. The remarkable capacity for microbes to evolve resistance is due to a combination of relatively quick doubling times and large population sizes, allowing bacteria to rapidly explore a diverse array of genetic possibilities and increasing the likelihood for a fortuitously beneficial variant to emerge. Without addressing this central law governing antibiotic resistance, the antibiotic arms race seems all but perpetual.Current antibiotic research has focused largely on developing new drugs that exhibit bactericidal activity through novel mechanisms. This has led to what is often referred to as the antibiotic arms raceHere we seek to highlight a potential therapeutic approach to tackling this fundamental problem in combating antibiotic resistance. Rather than focusing on the development of novel drugs utilizing alternative mechanisms for killing bacteria, this approach aims to devise co-therapies whose sole function is to potentiate the efficacy of existing antibiotic treatment. Crucially, such therapies must be designed to have minimal direct impact on bacterial fitness when administered independently. In doing so, these treatments should theoretically minimize inherent selective pressure for bacteria to evolve escape strategies that negate their impact.10. CRISPR has also been employed to interfere with the expression of target genes (CRISPRi) and has been explored for antibacterial applications11. Another tool for sequence-specific gene targeting are peptide nucleic acids (PNAs), single stranded DNA mimics that bind tightly to the corresponding antisense mRNAs12. PNAs have demonstrated effective antimicrobial activity when conjugated to cell-penetrating-peptide (CPP) motifs and targeted to knockdown gene expression17. Either of these approaches could be used to reduce expression of particular genes to enhance antibiotic killing.The design of such therapies has been made possible with recent advances in synthetic biology and the corresponding development of novel tools with sequence-specific targeting capabilities. This includes transcriptome editing based on clustered regularly interspaced short palindromic repeats (CRISPR)-associated endonucleases (such as Cas9), which has been employed as an antimicrobial to selectively degrade particular genetic elementsEscherichia coli, for which there exists a collection of every viable gene knockout18. Successful growth in the absence of these genes suggests that their loss provides a minimal fitness impact, fulfilling our first criteria of designing therapies that themselves are harmless to bacteria. Their existence also enables rapid screening of how analogous gene knockdowns will impact antibiotic efficacy. We focused on thirty stress-response gene knockouts that we identified to be differentially expressed during antibiotic exposure in our previous works20. We systematically characterized how each of the strains responded to growth in sub-minimum inhibitory concentrations (MICs) of nine commonly used antibiotics representing a broad spectrum of functional classes. From this we identified significant synergistic interactions and constructed CRISPRi constructs to replicate their results individually and in a multiplexed fashion. These constructs were also applied to Salmonella infections of HeLa cells to demonstrate their therapeutic potential in amplifying antibiotic efficacy. Finally, we utilize PNAs to knockdown these genes in four clinically isolated, MDR strains of bacteria.To design fitness-neutral potentiating therapies based on these technologies, we must first understand what genes to target. To this end, we began with a systematic exploration of gene-drug synergy in the well characterized bacteria Collectively, this study demonstrates a novel pipeline of synergistic drug discovery based on the perturbation of nonessential genes, progressing from knockouts, to perturbations, to infection models, and ultimately to PNA therapies. We show that this approach successfully re-sensitizes the bacteria to antibiotic treatment without imposing its own fitness cost. Together, these results demonstrate a new platform for discovering and designing synergistic therapies for enhanced antimicrobial treatment.21. Many studies have investigated E. coli response to various antibiotics, including the use of whole genome library knockouts24. Of the 4000+ genes in E. coli, these studies have identified a set of ~100-300 genes that influence the bacteria’s sensitivity to multiple antibiotics. This includes the tolC and acrA genes comprising the TolC-AcrAB efflux pump of E. coli, which has been frequently explored as a hub for targeting antibiotic resistance in these and many other studies29. Similarly, the transcriptional regulator marA, soxS, and rob have each been implicated in increasing E. coli antibiotic resistance32. Mutants of genes involved in the SOS response such as recA, dinB, polB, and dam are known to strongly influence E. coli response to antibiotics38. Additionally, a set of genes have been show to exhibit increased transcriptional activity during exposure to stressful environments in general, including rpoS, mutS, hfq, and cyoA44.We utilized the ample evidence in literature of genes associated with stress response and/or adaptation processes to narrow down a set of promising candidates for potentiating antibiotic activityfiu, tar, wzc, yjjZ were differentially expressed while ybjG, ydhY, ydiV, and yehS were differentially variable)20. In these studies, we also investigated the transcriptional regulators that control the genes exhibiting differential expression and narrowed down a set of novel targets . We reasoned that because these genes (or the downstream genes they regulate) exhibited particularly high gene expression variability during adaptation, they would serve as interesting candidates for targeting expression interference therapies towards.We have previously performed our own transcriptional analysis of bacteria adapting to stress response. Several genes were found to impact adaptive resistance in a transcriptome-level analysis of adapted versus unadapted strains , mutagenesis , motility , uncharacterized function (yjjZ and yehS), or general global regulation (the aforementioned others). Knockouts of gene were obtained from the Keio collection18. As E. coli is viable upon deletion of these genes, we reasoned that reducing expression of these non-essential genes is less likely to impose an inherent fitness cost compared to reducing expression of essential genes.Combining these two approaches, we developed a final set of thirty selected genes to explore as potential targets for antibiotic combination therapy Table . These g45.We chose to test these knockouts’ growth in a set of nine antibiotics representing a diverse set of common antimicrobial therapies Table . Growth S = WX*WY – WXY, based on bacterial fitness in the presence of antibiotic (WX), gene knockout (WY), or a combination of both (WXY). An example of this is presented in Fig. WX = 1.04 ± 0.06), nor did deletion of acrA (WY = 0.93 ± 0.03). However, BW25113-ΔacrA exposed to AMP demonstrated poor fitness (WXY = 0.07 ± 0.02), indicating potentiation of AMP activity by removing acrA (S = 0.89 ± 0.12). This process was repeated for all 269-remaining gene–drug pairs  then a one-sided t-test further determined synergism (P < 0.05) or antagonism (P > 0.05).We characterized BW25113 growth in 270 combinations of 30 Keio knockouts with these nine antibiotics. Synergy (S) between gene knockout and antibiotics was determined using the Bliss Independence model, irs Fig. . Drug inacrA, fur, recA, rpoS, and tolC) were found to potentiate activity of at least six out of nine antibiotics tested, suggesting that these genes are promising targets for co-therapies. Many of these gene knockout drug synergies, to the best of our knowledge, are novel discoveries, such as that between fnr and five of the antibiotics tested. Conversely, two gene knockouts (gadX and hfq) caused antagonism of at least seven of nine antibiotics and are thus poor candidates for antimicrobial potentiation purposes.We identified 90 gene–drug interactions which elicited synergistic interactions, and another 67 gene–drug interactions that resulted in antibiotic antagonism Fig. . Of the dam (WY = 0.49 ± 0.28), Δrob (WY = 0.48 ± 0.05), Δhfq (WY = 0.38 ± 0.04), and Δtar (WY = 0.41 ± 0.05). Δhfq and ΔgadX demonstrated consistent antagonism and were thus already not candidates for further screening.The goal of this systematic investigation was two-fold, the first of which was to identify strong gene–drug synergistic interactions. The second goal was to ensure that these knockouts imposed minimal fitness costs on cell growth, to protect against the possibility of natural selection working against sequence-specific therapies designed to target these genes. In order to avert development of gene knockdown therapies that pose a direct impact on cellular fitness in the absence of antibiotic exposure, we avoided gene knockouts that had particularly strong impacts on growth. This includes four gene deletions: ΔCollectively, these results point to promising targets for designing fitness-neutral gene expression perturbations that enhance antibiotic efficacy. We explore the development of such therapies utilizing CRISPR-Cas9 in a latter portion of the manuscript. However, this knockout-drug synergy screen also provides interesting conclusions regarding the general mechanisms of gene–drug synergy that we will now explore.47 stating that the degree of gene–drug synergy is influenced by the epistatic interactions the targeted gene is involved with. In particular, we have found that as more protein–protein interactions are disrupted by targeted genetic perturbations, a greater than expected detrimental fitness impact emerges. We applied a similar approach in this study to explore the known protein interaction networks of each of the thirty genes here to unravel similar underlying correlations. From the STRING database48, we extracted information of all the known and predicted protein–protein interactions for each gene to construct and quantify their protein interaction networks. We explored the total number of proteins interactions, i.e., the amount of nodes that are present . While correlation in itself does not prove a meaningful connection, its existence suggests that targeting nodes involved in broad protein interaction networks can lead to enhanced levels of gene–drug synergy. Additionally, two other studies from our lab have also found a similarly significant correlation between synergy and protein interactions47. Our previous work demonstrated that perturbing genes involved in broad protein interaction networks lead to strong negative epistatic effects. The data presented here supports this observation and lends further credence to the notion that epistasis plays a significant role in influencing bacterial fitness response towards co-therapies.We first explored the applicability of a hypothesis raised in our previous workent Fig. . We founwzc, represented one of the top three synergistic knockouts in ceftriaxone (CRO), erythromycin (ERY), and ciprofloxacin (CIP), but was also one of the three most antagonistic knockouts in sulfadimidine (SDI) and trimethoprim (TMP). Whole genome RNA-sequencing showed that wzc, a colanic acid biosynthesis gene, was overexpressed during AMP exposure20, although no significant synergy was observed between Δwzc and AMP in this experiment. Though the classes of antibiotics in which synergy was observed were diverse, clear antagonism emerged in the antibiotics related to DNA/RNA synthesis (sulfadimidine and trimethoprim).To further explore the mechanistic underpinnings of gene–drug interactions, antibiotics and genes were grouped into mechanisms of action and pathways respectively Fig. . NotablyrecA, Δdam, and ΔrpoS, which demonstrated high synergy with four, two, and two antibiotics, respectively. There was no clear relationship between the cellular processes these genes are involved in and the antibiotics’ modes of action.The TolC-AcrA efflux pump knockouts demonstrated some of the highest levels of gene–drug synergy. Knockouts of at least one of these genes was always one of the three most synergistic genetic changes for all the antibiotics tested, apart from the 50S targeting antibiotics ERY and chloramphenicol (CM). However, even in these antibiotics, both knockouts resulted in significant synergy. The remaining standout knockouts include ΔIf knocking out these genes resulted in significantly amplifying antibiotic potency, we hypothesized that lowering their expression without completely removing them from the genome might engender similar results while also demonstrating a more therapeutically viable application of gene–drug synergy. To this end, we developed CRISPR interference (CRISPRi) constructs to knockdown expression of genes showing significant antibiotic synergy. For this, catalytically dead Cas9 (dCas9) was employed to reduce mRNA production of the targeted gene, which was subsequently exposed to a variety of antibiotics to determine its potential for inducing gene–drug synergy Fig. .Fig. 3Ap49. One plasmid encoded expression of dCas9 under the anhydrous tetracycline (aTc)-inducible promoter, while the other encoded a unique single guide RNA (sgRNA). sgRNA targets were designed using criteria set forth in previous studies for successfully eliciting inhibition50. This includes targeting either within the first ~50 nucleotides of the gene’s open reading frame, or within the −35 to +1 site of the gene’s promoter sequence. The ability of six of these constructs  and other similarly designed constructs to inhibit gene expression have been verified in our previous studies using real-time quantitative PCR47. We also analyzed all potential off-targets for each of these constructs based on what constitutes most likely off-targets in E. coli, and outline each of them in Table S252. Of these, only four constructs  had potential off-targets of genes whose deletions are known to cause fitness defects. As the two plasmids used to express the CRISPRi constructs rely on AMP and CM selection markers, we excluded exploration of these antibiotics going forward. Additionally, due to the general low degree of synergy demonstrated by gene knockouts with SDI, this antibiotic was not included.We specifically focused on six of the genes showing the greatest degree of synergy with each of the antibiotics tested, while also maximizing the diversity of genetic pathways targeted for synergy with each antibiotic Table . We utilrfp) (which is not present in the strain) was used in lieu of wildtype BW25113 as the control. All fitness values were normalized to the growth of the control strain in the absence of any antibiotic. Fitness of the control strain was measured during exposure to each antibiotic (WX), each individual perturbation strain in the absence of antibiotic (WY), and each perturbation strain during antibiotic exposure (WXY). Experiments were again performed in M9 minimal media supplemented with 0.4% glucose and antibiotics as appropriate.The gene-antibiotic synergy experiments were again repeated, with CRISPRi employed in the place of gene knockouts. A strain expressing a sgRNA targeting the coding sequence of red fluorescent protein , three synergized with TMP  and CIP , and two synergized with puromycin (PURO) (acrA-i and tolC-i) and tetracycline (TET) (acrA-i and tolC-i). Three combinations with TET resulted in clear antagonism: rpoS-i, yehS-i, and crp-i. A few CRISPR perturbations did stand out from the rest in the clear antibiotic synergy they induced. Most notable is the degree of synergy induced by inhibitions of the tolC-acrA efflux pump in ERY , PURO , TET , and TMP . Inhibitions of recA and fnr additionally showed significant improvements in CIP efficacy . CRISPRi largely replicated gene knockout synergy with antibiotic treatment. A direct comparison of the synergy levels is presented in Fig. acrA-i and tolC-i combined with ERY treatment, and both fnr-i and recA-i combined with CIP treatment. Comparing synergy values between gene knockouts and CRISPRi gene perturbations showed a strong correlation (P = 0.003) Additionally, the average synergy across all perturbations was lower than the average synergy of corresponding gene knockouts during exposure to CRO , TET , ERY , PURO , and TMP . Lower levels of perturbation-antibiotic synergy relative to knockout-antibiotic synergy are unsurprising given that the target gene can still be expressed  in the former case.Despite this caveat for our control, the majority of CRISPRi perturbation co-therapies resulted in statistically significant potentiation of antibiotic treatment, suggesting that this was an effective strategy for replicating revealed knockout-drug synergy Fig. . Four petolC-i, ydhY-i, phoP-i, and marA-i), five with CIP , four with TET , two when targeting ERY (tolC-i and acrA-i), three when targeting TMP , and three when targeting PURO . While the majority of perturbations induced antibiotic synergy in at least one of the two environments tested, a few perturbations provided either no synergism or was antagonistic and are therefore not useful candidates for potential therapies. This includes targeting crp during CRO treatment, yehS during TET treatment, and both wzc and blgG during PURO treatment. These data sets provide quantification of gene-drug synergies in two environments. Taken together, these results highlight that CRISPRi can effectively potentate antibiotic treatment.To have a better understanding of these perturbations on antibiotic efficacy, we also performed growth curve analysis of each CRISPRi strain with their corresponding antibiotics in an alternative environment of LB media Figs. –9. In mo47. This suggests that multiplexing synergistic CRISPRi perturbations could exacerbate the potentiation of antibiotic efficacy. We took advantage of this by combining the six perturbations designed for each antibiotic into one construct and testing their impacts on BW25113 growth during antibiotic exposure.An advantage of CRISPRi is the relative ease in which individual perturbations can be combined into a single cell by including multiple sgRNAs in a CRISPR array. Furthermore, we have previously shown that multiplexing perturbations tends to exacerbate detrimental fitness impacts by inducing negative epistatic interactions between the perturbed genesrfp perturbations , CIP , and ERY . The strong synergy observed by multiplexed TET perturbations  is particularly notable given the varied levels of synergy observed when perturbations were applied individually.In stark contrast to this, every multiplexed CRISPRi perturbation strains designed for inducing synergy showed significant potentiation of antibiotic efficacy, apart from PURO perturbations Fig. . Synergy47. Furthermore, this potential problem would be alleviated in a therapeutic context by utilizing direct delivery of dCas9-sgRNA pre-assembled complexes. Regardless, these results support the conclusion that the designed multiplexed perturbations largely potentiate antibiotic treatment without imposing a substantial, direct impact on fitness, and provided direction as to which perturbation-antibiotic pairs to focus on for the remainder of our experiments.To further elucidate multiplexed perturbations’ impacts on BW25113 growth, we examined each strain’s growth profile over 20 h in both the presence and absence of antibiotic and compared these profiles to the multiplexed control perturbation strain Fig. . All strrfp perturbation was modified to constitutively express mCherry. The relative abundance of each multiplexed perturbed strain was equivalent to that of the control strain in the absence of antibiotic exposure, confirming that these perturbations have no direct impact on fitness   Fig. . CollectE. coli, the bacteria Salmonella enterica  or near-complete  homology to SL1344’s genome, and therefore are likely to maintain efficacy in this organism  . Strong synergy was also observed between ERY and the six-perturbation strain . Additionally, antagonism was observed between the three and six perturbations and CIP , which could be due to the antagonism demonstrated by ΔacrA and ΔcyoA in BW25113. Antagonism was also seen in the three-perturbation strain combined with ERY .No detrimental impact on basal SL1344 fitness was observed in the absence of antibiotics for either of these strains (ly) Fig. . SignifiGoing forward, we focused our efforts on characterizing these perturbations’ impacts on TET and TMP, as these antibiotics showed high levels of synergy. The growth profiles of each strain were characterized in the presence of no antibiotic, TET, or TMP Fig. . No impaSalmonella in the absence of antibiotic. Significant reductions in viable SL1344 were observed in the presence of TMP for both the three-gene (P = 0.04) and six-gene perturbation (P = 0.03) strains . These results indicate that the targeted multiplexed CRISPRi constructs successfully potentiated intracellular antibiotic treatment, supporting the therapeutic viability of fitness-neutral gene perturbation treatments.To investigate the ability of perturbations to potentiate antibiotic clearance of intracellular infections, HeLa epithelial cells were infected with each SL1344 strain. Infected HeLa were subjected to no antibiotic, 0.5 µg/mL TET, or 0.5 µg/mL TMP for 18 h of post infection. HeLa were subsequently lysed, and CFUs of intracellular SL1344 were determined. The surviving SL1344 in the presence of antibiotic were compared to the relative surviving ins Fig. . This wa12. When conjugated to CPPs, PNAs can readily cross bacterial membranes and enter the cell. When these PNAs enter the cell, they form tight bonds with complementary mRNA, preventing ribosome translation of these genes into proteins  phenotype, and two strains of Klebsiella pnuemoniae (KPN) producing either an extended spectrum β-lactamase (ESBL) or a New Delhi metallo-β-lactamase 1 (NDM-1). These strains have been found to survive a wide range of antibiotic concentrations significantly above the resistance breakpoint levels established by the Clinical & Laboratory Standards Institute (CLSI), including AMP, CIP, CM, TET, kanamycin (KAN), rifampicin, streptomycin, gentamicin (GEN), and clindamycin8. Additionally, we found each MDR strain to resist TMP levels well above the CLSI breakpoint of 2.0 µg/mL, while wildtype BW25113 exhibited sensitivity at 0.25 µg/mL  long PNA molecules to inhibit expression of the remaining four genes  by targeting them to overlap the start codon of each gene’s open reading frame. Target sequences are presented in Table We chose to focus specifically on synergy with TMP, as we achieved the greatest success in engineering synergy in a fitness-neutral fashion with this antibiotic in our CRISPRi approach. We first screened the genomes of the four MDR isolates for homology with each of the six TMP related gene perturbations tested with CRISPRi. Low homology was found for yrecA and fnr targeting PNA minimally reduced growth (<10% reduction) in both E. coli strains, while the csgD PNA minimally reduced growth in both E. coli strains and significantly reduced growth (>10% reduction) in ESBL KPN.We next examined the ability of the four targeted PNAs to synergize with TMP treatment in each of the four MDR bacterial strains Fig. . Again, recA combined with antibiotic treatment in ESBL KPN. Due to the variability seen in these clinical isolates no combination showed statistically significant synergy at three biological replicates. The five cases with positive S values above 0.25 correspond with the clinical isolates that showed at least one biological replicate having greater than 50% reduction in growth in combination treatment as compared to PNA treatment alone.For four out of the five instances where PNA showed a small (<10% reduction) impact on growth there is a greater than 50% reduction in growth for the combined PNA and antibiotic treatment condition as compared to PNA treatment alone for two out of the three biological replicates. Only one biological replicate showed greater than 50% reduction in growth for PNA targeting While these findings substantiate the perturbation-drug synergy discovery pipeline outlined throughout this study, the large variability in synergy (caused by one replicate) suggests the potential for escape. Further research is necessary to understand the underlying mechanisms for this phenomenon.Here we present a drug-discovery-pipeline for the identification of sequence-specific gene expression therapies that potentiate antibiotic treatments without directly affecting bacterial fitness. We utilize a gene knockout library to reveal promising gene candidates and build upon these results by engineering CRISPRi and PNA therapies to facilitate targeted gene knockdown. Many of these gene expression treatments were shown to illicit no fitness cost when administered independently yet were still successful in potentiating antibiotic killing. Finally, we demonstrate that this approach is reproducible in an intracellular-infection context and is effective at resensitizing clinically isolated MDR bacteria to antibiotic treatment. Together, these experiments outline a pipeline for discovering perturbation-drug synergies applicable to therapeutic contexts. Notably, this pipeline could easily be expanded to explore more perturbations and drugs, to enhance the number of successful synergistic therapies discovered at the final stage.59, these studies have not considered how identified gene–drug synergy can be therapeutically exploited to potentiate antibiotic efficacy, as we have done here. Likewise, previous studies examining how single gene disruption alters antibiotic fitness have lacked direct comparison to wild type controls, meaning that deleterious interactions cannot be defined as additive, synergistic, or antagonistic58. A lack of wild type performance data prevents other large-scale explorations of bacterial phenotype from being capable of typifying gene/drug interactions22. The work presented here, and similar efforts that use CRISPR-interference to perturb gene expression in the presence of stressful environments11, are critical to explore the widespread potential that synergistic, antagonistic, or additive interactions may have. Another key consideration in this study is the concern placed towards designing fitness-neutral therapies. The field of antibiotic synergy research is well established, and numerous reports have emerged of a correlation between the application of synergistic antibiotics and an acceleration in the rate of antibiotic resistance evolution60. Recent studies indicate that during simultaneous application of synergistic antibiotics, mutations conferring resistance to one antibiotic are selected for at a greater rate than they would be if similar levels of that antibiotic were administered independently61. This is because the fitness deficit applied by the second synergistic antibiotic strengthens the selective advantage a resistant mutation provides by imposing an additional fitness benefit that would be absent in the case of application of one antibiotic. Crucially, this phenomenon should work in both directions; the synergy of antibiotic “A” provides an additional selective advantage for a resistance mutation for antibiotic “B” to emerge and vice-versa.While previous studies have employed the Keio library to explore the impacts of gene knockouts on antibiotic efficacyIn our approach to developing fitness-neutral gene perturbations for inducing antibiotic synergy, the mutual selective advantage for the emergence of resistance mutations could theoretically be abated. A mutation providing resistance against the fitness-neutral gene perturbation has no selective pressure for propagating in the case of its independent application. Furthermore, in the case of co-application of the perturbation with an antibiotic, the selective advantage of a resistance mutation nullifying the impact of the perturbation will theoretically be less powerful, or indeed negligible, than a corresponding mutation for a fitness-impacting secondary antibiotic, ultimately decreasing the likelihood of such a mutation from emerging. In a clinical context, this would mean that fitness-neutral potentiating therapies could provide the enhanced killing caused by antibiotic synergy, while minimizing the potential for antibiotic resistance from emerging. Notably, the phenomenon of enhanced mutation rates caused by antibiotic synergy has only been considered between antibiotics that each exhibit a fitness impact on bacterial growth. To our knowledge, no study has considered how replacing one of these antibiotics with a fitness-neutral treatment would alter the rate of antibiotic resistance from emerging. Further experiments utilizing the approach outlined in this study could explore this theory in future work.62. While essential genes interference therapies can be developed, the likelihood that their inherent deleterious effects on fitness will encourage the evolution of new resistance requires significant consideration. The potentiating CRISPRi and PNA knockdowns of gene expression provides a promising approach to enhance our ability to treat MDR bacteria in the clinic without selecting for further resistance. This strategy is supported by a similar approach in which interference of LexA activity was applied to reduce expression of dinB, polB, and umuD, resulted in significant potentiation of CIP and rifampicin treatment during a long-term treatment63.The targeting of nonessential pathways to combat antibiotic resistance is an underexplored strategy in the literature, despite its potential for potentiating treatment without having an effect on pathogens on their own66. While multiple environmental conditions including an infection model were explored in this study, follow up studies utilizing more thorough exploration in diverse environments, including in vivo mammalian models beyond the HeLa cell infections used in Fig. It is well known that the local environment can affect a therapy’s efficacyE. coli18, many of which could hold promise as targets for fitness neutral potentiation of antibiotic therapy. Work in our lab has suggested that multiplexing gene perturbations can restrict the evolvability of bacteria. Through our approach, dubbed Controlled Hindrance of Adaptation of OrganismS or CHAOS, combinatorial gene expression knockdowns are introduced to disrupt adaptive pathways by eliciting negative epistatic interactions. This strategy has been demonstrated to significantly slow the increase in antibiotic MICs that bacterial populations could survive over time47. The data presented here suggests that the CHAOS approach might also facilitate resensitization of antibiotic resistant bacteria to treatment, while concurrently inhibiting the emergence of novel antibiotic resistance. Taken together, we are optimistic about the potential of gene/drug combination therapies to realize promising candidates with clinical relevance for combating antibiotic resistance.Finally, the pool of genes that can be explored for gene-drug synergies is vast and remains largely untapped. Here we explored only 30 of the reported 3985 nonessential genes of recA, polB, dinB, and dam), general stress response , and mar regulon  genes during adaptation19. Several of the genes selected here were also found to impact adaptive resistance in a transcriptome-level analysis of adapted versus unadapted strains 20. Finally, we looked upstream and selected transcriptional regulators that control the expression of these and other genes . The selected genes represent diverse functionalities, including transport , mutagenesis , motility , general global regulation , and include a few targets with unknown function (yjjZ and yehS).We selected thirty genes to evaluate as potential targets for combination therapy. Many of these genes were chosen due to existing evidence of their association with stress response and/or adaptation processes. We previously quantified the behavior of certain SOS response (18. The parent strain (Escherichia coli BW25113) and individual gene knockouts were obtained from Yale’s Coli Genetic Stock Center . E. coli NEB 10-β was used for cloning of all CRISPR plasmids used in this study. Experiments using plasmids were done by transforming these plasmids into E. coli BW25113. Salmonella enterica serovar Typhimurium SL1344 with genome-integrated Green Fluorescent Protein (GFP) was used for harboring CRISPR plasmids for intracellular infections.All knockout strains used are from the Keio collectionE. coli, another multidrug resistant E. coli, Klebsiella pnuemoniae harboring New Delhi metallo-β-lactamase 1 (NDM-1), Klebsiella pnuemoniae harboring extended-spectrum β-lactamase (ESBL)55.Clinical isolates of multidrug resistant bacteria were obtained from the lab of Dr. Nancy Madinger at the University of Colorado Anschutz campus. This includes carbapenem-resistant Enterobacteriaceae (CRE) 4, 0.1 mM CaCl2, and 0.4% glucose. Experiments performed using cation-adjusted Mueller Hinton Broth (caMHB) contain MHB supplemented with magnesium and calcium ions. Keio collection strains were grown in the presence of 40 µg/mL kanamycin (KAN). Strains harboring CRISPR plasmids were grown in the presence of 100 µg/mL ampicillin (AMP) and 35 µg/mL chloramphenicol (CM) and supplemented with 50 ng/mL anhydrous tetracycline (aTc) for induction of dCas9 when appropriate. All liquid cultures were grown at 37 °C with 225 rpm shaking, and all plating was performed at 37 °C.Unless otherwise noted, all experiments using these strains were performed in Lysogeny broth (LB). Experiments performed using M9 minimal media were supplemented with 2.0 mM MgSOAMP, ceftriaxone (CRO), gentamicin (GEN), KAN, puromycin (PURO), and sulfadimidine (SDI) were prepared with water as a solvent. Tetracycline (TET), erythromycin (ERY), and CM were suspended in 70%, 100%, and 100% ethanol, respectively. Ciprofloxacin (CIP) was prepared in water with HCl added drop by drop until the powder became soluble. Trimethoprim (TMP) was suspended in DMSO. All antibiotics were stored in aliquots at −20 °C.600 = 1. A 1:100 dilution was used to inoculate 50 μL cultures in M9 minimal media containing one of ten concentrations for each antibiotic (in two-fold increments) as well as controls without antibiotic. Optical density (OD) was monitored in a GENios plate reader (Tecan Group Ltd.) operating under Magellan software (version 7.2), with measurements taken every 20 min. The microplate reader was set to shake for 1000 s, with 10 s of shaking before measurement. The concentration selected for each antibiotic was that at which maximum OD was between 50–90% that of the control  or OD580 = 1  and diluted 1:100 into 50 µL cultures in M9 media containing either no antibiotic or the specified concentration of each antibiotic. Four biological replicates were included for each condition. OD was monitored in a Tecan GENios microplate reader as described above. The maximum OD600 (for Keio strains) or OD580  achieved for each well was recorded and used for subsequent characterization of the nature of the interaction.BW25113 and single gene knockout mutants were plated from glycerol stocks. Colonies from each were used to inoculate 1 mL cultures in M9 minimal media with 0.4% glucose and grown for 16 h. Samples were then normalized to ODSalmonella strains harboring CRISPR perturbations, except M9 media was replaced with LB media.BW25113 harboring an RFP-targeting sgRNA was used as a nonsense wild type control for comparing the impact of perturbations, as this guide has no significant homology to the genomes of any strain used in this study. This strain, as well as single and multiplexed gene perturbation mutants were plated from glycerol stocks, and 20–22 individual colonies were used to inoculate 100 µL cultures in M9 minimal media with 0.4% glucose and AMP and CM selection. Cultures were grown for 16 h and diluted 1:100 into 100 µL cultures containing 50 ng/mL aTc and either no antibiotic or the specified concentration of each antibiotic. ODs were monitored in a Tecan GENios microplate reader as described above, and the maximum OD achieved for each well was recorded and used for subsequent characterization of the nature of the interaction. This same process was used for characterizing synergy of CRISPR strains harboring either six copies of RFP sgRNA perturbations, multiplexed TET or TMP synergistic gene perturbations, or a single RFP sgRNA perturbation and constitutively expressed mCherry were plated from glycerol stocks. Eight biological replicates of each strain were used to inoculate 200 µL LB cultures supplemented with AMP and CM and grown for 16 h. Samples were then diluted 1:100 into fresh media supplemented with AMP, CM, and 50 ng/mL aTc, and grown for another 24 h. Competition began by mixing 1 µL of the mCherry control strain with one µL of the competitor strain in 198 µL of the noted condition. Conditions always included LB supplemented with AMP and CM, three conditions with 50 ng/mL aTc, and another three conditions without aTc. Each condition was supplemented with either no additional antibiotic, 0.25 µg/mL TET, or 0.125 µg/mL TMP. Two microliter of each culture were used immediately to determine starting ratios of red to white cells. The remaining culture was grown for 24 h, diluted again 1:100 in fresh media, and grown for another 24 h, after which 2 µL was again used to determine ending ratios of red to white cells.ω) using the standard Malthusian fitness equation, using the formula ω = ln(NE1 × 1002/NE0)/ln(NC1 × 1002/NC0)67 where the variables are defined as follows: “N”—colony forming units (cfu), “E”—experimental strain, “C”—control strain, “1”—after exposure, and “0”—before exposure.Ratios were determined by plating 50 µL of 1:10,000 and 1:100,000 on plain LB plates. Two plate images were taken with fluorescence activation at 540 nm, one with emission filtering at 590 nm and the other without, and these images were overlaid to facilitate colony counting. Colony counts were used to determine fitness values (600 (for Keio collection strains) or OD580  reached in the presence or absence of antibiotic and gene knockouts/perturbations were then used to determine the degree of synergy. If dΦ is the maximum OD of BW25113 wild type in media without antibiotic, dA is the ODmax of the wild type with antibiotic treatment, dK is that of the mutant without antibiotic, and dAK is that of the mutant with antibiotic, then ODmax can then be normalized as WX = dA/dΦ, WY = dK/dΦ, and WXY = dAK/dΦ. Similarly, for gene perturbation experiments, if dΨ is the maximum OD of the control perturbation strain in media without antibiotic, dX is the ODmax of the control strain with antibiotic treatment, dY is that of the perturbation without antibiotic, and dXY is that of the perturbation with antibiotic, then ODmax can then be normalized as WX = dX/dΨ, WY = dY/dΨ, and WXY = dXY/dΨ. Furthermore, the degree of interaction synergy (S) was identified using the equation S = WX * WY – WXY.The maximum values of ODCRISPR expression was driven from two plasmids, one encoding for aTc-inducible dCas9 (Addgene plasmid 44249), and another encoding for constitutively expressed sgRNA targets derived from Addgene plasmid 44251. The latter plasmid was used to create new sgRNA target plasmids by replacing the RFP-targeting sequence with new gene sequences specific to the target of interest. Unique forward primers flanked with a SpeI restriction site and encoding the new target sequence and a common reverse primer flanked with ApaI was used to PCR amplify  new DNA inserts, which were subsequently digested with CutSmart SpeI and ApaI (New England Biolabs) alongside 44251 backbone. Ligation of these pieces was performed using T4 DNA Ligase (Thermo Scientific), which were subsequently transformed into electrocompetent NEB 10-β. Plasmids from transformants were recovered using the Zyppy Plasmid Miniprep Kit (Zymo Research Corporation) and submitted for sanger sequencing to confirm successful insertion (GENEWIZ). These final plasmids were co-transformed alongside the dCas9 plasmid into BW25113 to create the final CRISPR individual perturbation strains. The specific sgRNA target sequences are presented in Table To create multiplexed gene perturbation strains, Gibson assembly was used to sequentially stich individual sgRNAs together. A common set of six forward and six reverse primers were used to amplify sgRNAs as Gibson fragments, beginning with stitching sgRNAs together in pairs. Once the paired sgRNA plasmids were confirmed, two of the three pairs for each set were stitched together using another round of Gibson assembly. Finally, once these four sgRNAs were confirmed, the final pair of sgRNAs were stitched together with this four-target sgRNA construct using a final round of Gibson assembly. Final plasmid sizes were confirmed, and then transformed into BW25113 or SL1344 for experiments. All Gibson reactions were performed at 50 °C for 1 h with T5 exonuclease (New England Biolabs), Phusion polymerase and Taq ligase (New England Biolabs). This process was used to create the multiplexed six-gene targeting sgRNA constructs.To demonstrate growth curves, at least five biological replicates of each strain were inoculated from individual colonies into 200 µL of LB containing AMP and CM in a conical 96-well microplate and grown for 16 h. After initial growth, 2 µL of each culture was used to inoculate 198 µL of fresh media containing AMP, CM, and conditionally aTc or antibiotics as noted. These cultures were grown in a flat bottom 96-well microplate in a Tecan GENios microplate reader for 24 h as described above.48. The acquired counts of network nodes, node degrees, edges, and the overall cluster coefficient of the protein network were extracted directly from the database. A minimum confidence score of 0.40 was used to collect information from experiments, databases, co-expression, co-occurrence, gene fusions, and gene neighborhoods. The maximum number of interactions was set to 250 for the first shell and zero for the second shell.Data for the protein–protein interaction networks presented in Fig. 2 and controlled humidity, and media was changed every two-three days with subculturing at 80% confluency with 0.25% trypsin (HyClone). HeLa were used for infection three passages after starting from a freezer stock, and all experiments were performed with HeLa between passages 8 and 12. At 24 h prior to infection, HeLa were trypsinized off of tissue culture flasks and seeded into a 96-well tissue culture treated plate (Fisher Scientific) at 10,000 cells/mL in 100 µL full growth media.HeLa human epithelial cells were recovered from freezer stocks in 10% dimethyl sulfoxide  and full growth media consisting of Dulbecco’s modified Eagle medium , 10% fetal bovine serum , and 50 units/mL penicillin-streptomycin . A single freezer stock at passage number six was split into three separate tissue culture flasks maintained as separate biological replicates. Cells were maintained at 37 °C with 5% CO580. HeLa cells were washed three times with Dulbecco’s PBS  and incubated in DPBS containingSL1344 for 45 min at 37 °C with 5% CO2 and controlled humidity. After 45 min of infection media was replaced with DMEM+ FBS+ 100 µg/mL GEN and incubated for another 75 min to remove extracellular bacteria. A final media replacement was done with full growth media  in either the presence or absence of 0.5 µg/mL TET or 0.5 µg/mL TMP and incubated for 18 h. To perform CFU analysis, HeLa cells were washed with DPBS thrice and lysed with 30 µL of 0.1% triton X-100 for 15 min at room temperature, after which 270 µL of PBS was added to each well and plated on plain LB agar to determine CFUs.The night before infection, SL1344 was inoculated from plates into 3 mL LB with AMP and CM selection and grown for 16 h. Cultures were then diluted 1:10 in LB with AMP and CM and grown for another four hours, after which samples were washed three times with PBS and normalized to the same OD17, and they consist of a KFFKFFKFFK cell-penetrating-peptide (CPP) sequence on the N-terminus, followed by an “O-linker” sequence connecting the CPP to the 12-mer nucleoside sequences with a peptide backbone. These PNA sequences were optimized to exhibit minimal off-target effects in the BW25113 genome (REFSeq: GCF_000750555.1) using a custom program described below. As recA exhibited an off-target around the start codon of the ndk gene, this PNA was redesigned to bind within the first 12 nts of the recA gene, beginning with the start codon. PNA sequences were also analyzed for their ability to bind to the genome of each of the clinically isolated MDR bacteria. All PNAs were found to have at least one possible target sequence in each of the MDR bacteria. PNAs were purchased from PNA Bio, and their sequences are presented in Table PNA sequences were designed to bind in a centered region of the mRNA AUG start codons for the genes of interest. These 12-mer sequences were synthesized using a semi-automated platform published previously17. Briefly, a custom Python 3.7 script17 was used to extract the reverse complements of 12-mer nucleotide sequences centered on the mRNA AUG start codons (STC) for genes of interest. Homology was determined using the Bowtie 2 (version 2.3.5.1) short-read alignment tool68, allowing for one nucleotide mismatch within the sequence alignment. The BEDTools (v2.25.0)69 “intersect” function was used to identify alignments that overlapped with genome features, and a custom Python script was used to parse this data and calculate the alignments’ proximities to gene STCs. Off-target or homology inhibition was defined as a sequence alignment overlapping the STC of a gene that the PNA was not specifically designed to inhibit. Thermodynamic considerations for PNA sequences were screened for using a custom Python script designed to search for potential solubility and self-interference issues. The former was addressed by looking for purine stretches greater than five bases, a purine content of greater than 50%, or a guanine-peptide content of greater than 35%. The latter was addressed by looking for self-complementary sequences of greater than five bases.Our PNA Finder bioinformatics toolbox was used to design the PNA sequences, as published previously580 values were subtracted. Maximum OD values were recorded for each condition and normalized to the maximum OD of the no treatment.Three biological replicates of BW25113 and MDR strains were inoculated from individual colonies in 3 mL caMHB and grown overnight for 16 h. Strains were then diluted 1:10,000 in fresh caMHB and aliquoted in 45 µL to a 384-well plate, to which 5 µL of 100 µM PNA treatment of interest was added . Samples were grown for 24 h in a GENios microplate reader as described above to track growth over time. Blank wells and minimum OD46. Briefly, treatment independence was determined first by a two-sided t-test, after log transformation of the data. If the interaction was statistically significant (P < 0.05) then a one-sided t-test was used to determine if the interaction was synergistic (P < 0.05) or antagonistic (P > 0.05). Pearson correlation coefficients and their corresponding P values were calculated using linear fits with no weighting (OriginPro 9.3.226 software). All other P values reported were calculated using a standard two-tailed type II student’s t-test. Standard deviations were estimated using appropriate propagation of error formulas excluding covariance terms.To determine if a gene knockout–drug interaction was synergistic, additive, or antagonistic we followed the statistical analysis as described by Demidenko et al.Further information on research design is available in the Peer Review FileSupplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Reporting Summary


Nucleotide metabolism plays a central role in bacterial physiology, producing the nucleic acids necessary for DNA replication and RNA transcription. Recent studies demonstrate that nucleotide metabolism also proactively contributes to antibiotic-induced lethality in bacterial pathogens and that disruptions to nucleotide metabolism contributes to antibiotic treatment failure in the clinic. As antimicrobial resistance continues to grow unchecked, new approaches are needed to study the molecular mechanisms responsible for antibiotic efficacy. Here we review emerging technologies poised to transform understanding into why antibiotics may fail in the clinic. We discuss how these technologies led to the discovery that nucleotide metabolism regulates antibiotic drug responses and why these are relevant to human infections. We highlight opportunities for how studies into nucleotide metabolism may enhance understanding of antibiotic failure mechanisms. In the nearly 100 years since the discovery of penicillin, antibiotics have revolutionized medical practice and have become a cornerstone of modern medicine. However, growing rates of antimicrobial resistance pose an urgent and looming threat to public health and economic stability , creatinClinical microbiology traditionally relies on general microbiology and molecular biology laboratory techniques, such as polymerase chain reaction and gene deletion/over-expression, to elucidate molecular mechanisms responsible for clinical phenotypes. However, experimental throughput by these methods limits progress toward understanding mechanisms of antibiotic treatment failure. In recent years several new experimental and digital technologies have emerged with promise to increase clinical microbiology laboratory throughput and enhance clinical management of bacterial infections –5. MoreoHere, we review emerging digitalization technologies poised to transform research into mechanisms of antibiotic treatment failure in the clinic. We describe several antibiotic resistance, tolerance and persistence mechanisms discovered from clinical strains. We discuss in detail the recent discovery that nucleotide metabolism actively participates in antibiotic lethality and the clinical relevance of these findings . We propin vitro screening with standardized antibiotics.The most important goal in clinical microbiology is to identify an infectious pathogen and determine its drug susceptibility profile . TraditiIn vitro studies in research settings have enabled the discovery of antibiotic resistance mechanisms. For example, following the initial detection of clinical tetracycline resistance, several microbiology studies identified decreased drug transport as the mechanism responsible for reduced efficacy (Escherichia coli and MexB in Pseudomonas aeruginosa)  . As withIn recent years, advances in laboratory evolution, high-throughput sequencing, and computational biology have greatly expanded the scope of addressable questions in microbiology and the study of antibiotic resistance . For insE. coli O104:H4 resulted in over 3,000 infections and more than 50 deaths – rapid, open-access whole-genome sequencing analysis revealed the phylogenetic relationships between this strain and 40 previously published pathogen genomes  in comparison to strains from patients durably cured  and antibiotic persistence , also lead to treatment failure and relapsed infection . AdditioIt is clear that antibiotic-target interactions alone are insufficient for explaining antibiotic treatment failure in human patients. To address these knowledge gaps, interpretable machine learning approaches are being developed, which seek to rapidly generate experimentally testable hypotheses for biological phenomena. In one of the earliest demonstrations of these, a biochemical screen was performed to measure changes in antibiotic efficacy following metabolic stimulation, and genome-scale metabolic modeling simulations were performed to estimate metabolic reaction activities in each screening condition . By applM. tuberculosis strains, novel metabolic resistance mechanisms to first-line tuberculosis antibiotics were discovered  as a shared substrate to the purine and pyrimidine biosynthesis pathways ppGpp function as universal alarmones for transcriptionally activating the stringent response and other bacterial stress responses as evolutionally conserved strategies for surviving nutrient limitation and other environmental stressors , 67. Intin vivo pathogenesis of diverse bacterial infections, and may be required for a pathogen's growth and survival within the host environment (S. aureus cells with transposon insertions in purB fail to establish bone infections in mice (E. coli from expanding into intracellular bladder epithelial cells (in vivo studies of methicillin-resistant S. aureus showed that purine biosynthesis was causally linked to survival during endovascular infection (It is interesting to note that nucleotide metabolism is also very important for the ironment . For ins in mice  and deleal cells . Likewisnfection . CollectThe growing challenge of clinical antibiotic failure demands renewed attention into the study of antibiotic mechanisms of action and the discovery of new antimicrobial compounds. Digital technologies such as whole-genome sequencing, machine learning, mass spectrometry and predictive modeling are likely to transform the clinical management of bacterial infections in the coming decades. Exciting developments in machine learning are, for the first time, enabling the rapid discovery of novel classes of antimicrobial compounds  and the The discovery that nucleotide metabolism is involved in antibiotic efficacy has several translational implications. Unlike the Mueller-Hinton or Luria-Bertani media commonly used by clinical and academic microbiology laboratories, the metabolic microenvironment of a bacterial infection is dynamically enriched for nucleotide metabolites during infection . In factNucleotide metabolism is one of the oldest areas of bacterial physiology to be investigated, with early studies into bacterial purine and pyrimidine metabolism predating the discovery of the lac operon , 81. IntConcurrently, new digitalization techniques are becoming increasingly democratized and are poised to transform our basic and translational understanding of how nucleotide metabolism may contribute to antibiotic efficacy. Advances in predictive modeling  and non-AL and JY planned, wrote, and edited the manuscript. All authors critically read, reviewed, and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.