Phagocytes, Antibiotics, and Self-Limiting Bacterial Infections

Allosteric inhibitor of SHP2 enhances macrophage endocytosis and bacteria elimination by increasing caveolae activation and protects against bacterial sepsis

The uncontrolled bacterial infection-induced cytokine storm and sequential immunosuppression are commonly observed in septic patients, which indicates that the activation of phagocytic cells and the efficient and timely elimination of bacteria are crucial for combating bacterial infections. However, the role of dysregulated immune cells and their disrupted function in sepsis remains unclear. Here, we found that macrophages exhibited the impaired endocytosis capabilities in sepsis by Single-cell RNA sequencing and bulk RNA sequencing. Caveolae protein Caveolin-1 (Cav-1) of macrophages was inactivated by SHP2 rapidly during Escherichia coli (E.coli) infection. Allosteric inhibitor of SHP2 effectively maintains Cav-1 phosphorylation to enhance macrophage to endocytose and eliminate bacteria. Additionally, TLR4 endocytosis of macrophage was also enhanced upon E.coli infection by SHP099, inducing an increased and rapidly resolved inflammatory response. In vivo, pretreatment or posttreatment with inhibitor of SHP2 significantly reduced the bacterial burden in organs and mortality of mice subjected E.coli infection or CLP-induced sepsis. The cotreatment of inhibitor of SHP2 with an antibiotic conferred complete protection against mortality in mice. Our findings suggest that Cav-1-mediated endocytosis and bacterial elimination may play a critical role in the pathogenesis of sepsis, highlighting inhibitor of SHP2 as a potential therapeutic agent for sepsis.

Polyphasic Characterization of Brucella spp. in Livestock Slaughtered from Abattoirs in Eastern Cape, South Africa

In livestock, brucellosis is mainly an asymptomatic disease except when abortion occurs; therefore, two serological tests are used for diagnosis as no single test is suitable. Abattoir samples enable a combination of culture, molecular, and serological tests to detect brucellosis. This study assessed Brucella-specific PCR (ITS-PCR) to detect brucellosis and to conduct a molecular characterization of Brucella spp. isolated from PCR-positive livestock (n = 565) slaughtered at abattoirs and the appropriate sample tissue(s). ITS-PCR detected Brucella DNA in 33.6% of cattle, 14.5% of sheep, and 4.7% of pig tissues. Impure Brucella cultures from PCR-positive tissues were 43.6% (44/94) of cattle, 51.7% (15/29) of sheep, and 50% (2/4) of pigs with predominantly B. abortus identification with AMOS-PCR and low isolation of mixed B. abortus and B. melitensis in all species. In cattle, 33% of isolates were from lymph nodes, while in sheep 38.0% were from the liver and kidney and only from tonsils in pigs (2/4). Brucella infections identified with AMOS-PCR were present in seropositive and mainly seronegative (75.6-100%) livestock with the potential to cause brucellosis during pregnancy or breeding. This study demonstrated the value of the polyphasic approach, especially with chronic infections and the potential risk of these asymptomatic animals.

Phage-Ce6-Manganese Dioxide Nanocomposite-Mediated Photodynamic, Photothermal, and Chemodynamic Therapies to Eliminate Biofilms and Improve Wound Healing

Biofilms have become one of the fundamental issues for chronic infections, while traditional therapies are often ineffective in removing quiescent (persister) cells from biofilms, resulting in a variety of implant-related or nosocomial infections. Recently, bacteriophage (phage) therapy has reflourished in research and clinical trials. However, phage therapy alone manifested many intrinsic defects, including poor biofilm penetration, incomplete clearance of quiescent cells, etc. In this study, a phage-Chlorin e6 (Ce6)-manganese dioxide nanocomposite (PCM) was constructed by mild biomineralization. The results demonstrated that PCM contained both the vigorous activities of host bacterial targeting and efficient delivery of Ce6 to penetrate the biofilm. Assisted with NIR irradiation, robust reactive oxygen species (ROS) was triggered within the biofilm. In the weak acidic and GSH-rich infection niche, PCM was degraded into ultra-small nanosheets, endowing PCM with moderate photothermal therapy (PTT) effects and considerable Mn²⁺ release, thus exerting strong chemodynamic therapy (CDT) effects in situ. In vivo application demonstrated that the combination of PCM application and NIR irradiation strikingly reduced the pathogen loading, activated innate and adaptive immunity, promoted neocollagen rearrangement, and attenuated cicatricial tissue formation. Our research may pave a new way for bacterial treatment, biofilm-related infections, and other diseases caused by bacteria.

Effect of Probiotic Supplementation on Gut Microbiota in Patients with Major Depressive Disorders: A Systematic Review

There is accumulating evidence on the beneficial effects of probiotic supplementation for patients with depressive disorders. However, prior reviews on the topic have largely focused on clinical effectiveness with limited emphasis on the underlying mechanisms of action and effects of probiotics on gut microbiota. In accordance with PRISMA guidelines, a systematic literature search of Medline, EMBASE and the Cochrane Library using combinations of the key words, (“depress*” OR “MDD” OR “suicide”), (“probiotic” OR “Lactobacillus” OR “Bifidobacterium”) AND (“gut” OR “gut micr*” OR “microbiota”), as well as grey literature was performed. We found seven clinical trials involving patients with major depressive disorder (MDD). The small number of studies and heterogeneous sources of data precluded meta-analysis. Most trials (other than one open-label trial) had a low-to-moderate risk of bias, which was largely due to a lack of control for the effects of diet on gut microbiota. Probiotic supplementation yielded only modest effects on depressive symptoms and there were no consistent effects on gut microbiota diversity, and in most instances, no significant alterations in gut microbiota composition were observed after four to eight weeks of probiotic intervention. There is also a lack of systematic reporting on adverse events and no good longer-term data. Patients with MDD may require a longer time to show clinical improvement and the microbial host environment may also need longer than eight weeks to produce significant microbiota alterations. To advance this field, further larger-scale and longer-term studies are required.

Antimicrobial resistance: new insights and therapeutic implications

Antimicrobial resistance has not been a new phenomenon. Still, the number of resistant organisms, the geographic areas affected by emerging drug resistance, and the magnitude of resistance in a single organism are enormous and mounting. Disease and disease-causing agents formerly thought to be contained by antibiotics are now returning in new forms resistant to existing therapies. Antimicrobial resistance is one of the most severe and complicated health issues globally, driven by interrelated dynamics in humans, animals, and environmental health sectors. Coupled with various epidemiological factors and a limited pipeline for new antimicrobials, all these misappropriations allow the transmission of drug-resistant organisms. The problem is likely to worsen soon. Antimicrobial resistance in general and antibiotic resistance in particular is a shared global problem. Actions taken by any single country can adversely or positively affect the other country. Targeted coordination and prevention strategies are critical in stopping the spread of antibiotic-resistant organisms and hence its overall management. This article has provided in-depth knowledge about various methods that can help mitigate the emergence and spread of antimicrobial resistance globally. KEY POINTS: • Overview of antimicrobial resistance as a global challenge and explain various reasons for its rapid progression. • Brief about the intrinsic and acquired resistance to antimicrobials and development of antibiotic resistance in bacteria. • Systematically organized information is provided on different strategies for tackling antimicrobial resistance for the welfare of human health.

SARS-CoV-2-associated gut microbiome alteration; A new contributor to colorectal cancer pathogenesis

The emergence of a novel coronavirus, COVID-19, in December 2019 led to a global pandemic with more than 170 million confirmed infections and more than 6 million deaths (by July 2022). Studies have shown that infection with SARS-CoV-2 in cancer patients has a higher mortality rate than in people without cancer. Here, we have reviewed the evidence showing that gut microbiota plays an important role in health and is linked to colorectal cancer development. Studies have shown that SARS-CoV-2 infection leads to a change in gut microbiota, which modify intestinal inflammation and barrier permeability and affects tumor-suppressor or oncogene genes, proposing SARS-CoV-2 as a potential contributor to CRC pathogenesis

Ventilator-Associated Pneumonia, Multidrug-Resistant Bacteremia and Infection Control Interventions in an Intensive Care Unit: Analysis of Six-Year Time-Series Data

Ventilator-associated pneumonia (VAP) occurs more than 48h after mechanical ventilation and is associated with a high mortality rate. The current hospital-based study aims to investigate the association between VAP rate, incidence of bacteremia from multidrug-resistant (MDR) pathogens, and infection control interventions in a single case mix ICU from 2013 to 2018. Methods: The following monthly indices were analyzed: (1) VAP rate; (2) use of hand hygiene disinfectants; (3) isolation rate of patients with MDR bacteria; and (4) incidence of bacteremia/1000 patient-days (total cases, total carbapenem-resistant cases, and carbapenem-resistant Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae cases separately). Results: Time trends of infection control interventions showed increased rates in isolation of patients with MDR pathogens (p <0.001) and consumption of hand disinfectant solutions (p =0.001). The last four years of the study an annual decrease of VAP rate by 35.12% (95% CI: −53.52 to −9.41; p =0.01) was recorded, which significantly correlated not only with reduced trauma and cardiothoracic surgery patients (IRR:2.49; 95% CI: 2.09−2.96; p <0.001), but also with increased isolation rate of patients with MDR pathogens (IRR: 0.52; 95% CI: 0.27−0.99; p = 0.048), and hand disinfectants use (IRR: 0.40; 95% CI: 0.18−0.89; p =0.024). Conclusions: Infection control interventions significantly contributed to the decrease of VAP rate. Constant infection control stewardship has a stable time-effect and guides evidence-based decisions.

Combination of in vivo phage therapy data with in silico model highlights key parameters for pneumonia treatment efficacy

The clinical (re)development of bacteriophage (phage) therapy to treat antibiotic-resistant infections faces the challenge of understanding the dynamics of phage-bacteria interactions in the in vivo context. Here, we develop a general strategy coupling in vitro and in vivo experiments with a mathematical model to characterize the interplay between phage and bacteria during pneumonia induced by a pathogenic strain of Escherichia coli. The model allows the estimation of several key parameters for phage therapeutic efficacy. In particular, it quantifies the impact of dose and route of phage administration as well as the synergism of phage and the innate immune response on bacterial clearance. Simulations predict a limited impact of the intrinsic phage characteristics in agreement with the current semi-empirical choices of phages for compassionate treatments. Model-based approaches will foster the deployment of future phage-therapy clinical trials.

Chronic systemic low-grade inflammation and modern lifestyle: the dark role of gut microbiota on related diseases with a focus on pandemic COVID-19

Inflammation is a physiological, beneficial and auto-limiting response of the host to alarming stimuli. Conversely, a chronic systemic low-grade inflammation (CSLGI), known as a long-time persisting condition, causes organs and host tissues' damage, representing a major risk for chronic diseases. Currently, a worldwide a high incidence of inflammatory chronic diseases is observed, often linked to the lifestyle-related changes occurred in the last decade's society. The mains lifestyle-related factors are a proinflammatory diet, psychological stress, tobacco smoking, alcohol abuse, physical inactivity, and finally indoor living and working with its related consequences such as indoor pollution, artificial light exposure and low vitamin D production. Recent scientific evidences found that gut microbiota (GM) has a main role in shaping the host's health, particularly as CSLGI mediator. As a matter of facts, based on the last discoveries regarding the remarkable GM activity, in this manuscript we focused on the elements of actual lifestyle that influence the composition and function of intestinal microbial community, in order to elicit the CSLGI and its correlated pathologies. In this scenario, we provide a broad review of the interplay between modern lifestyle, GM and CSLGI with a special focus on the COVID symptoms and emerging long-COVID syndrome.

Psychological Symptoms in COVID-19 Patients: Insights into Pathophysiology and Risk Factors of Long COVID-19

There is growing evidence of studies associating COVID-19 survivors with increased mental health consequences. Mental health implications related to a COVID-19 infection include both acute and long-term consequences. Here we discuss COVID-19-associated psychiatric sequelae, particularly anxiety, depression, and post-traumatic stress disorder (PTSD), drawing parallels to past coronavirus outbreaks. A literature search was completed across three databases, using keywords to search for relevant articles. The cause may directly correlate to the infection through both direct and indirect mechanisms, but the underlying etiology appears more complex and multifactorial, involving environmental, psychological, and biological factors. Although most risk factors and prevalence rates vary across various studies, being of the female gender and having a history of psychiatric disorders seem consistent. Several studies will be presented, demonstrating COVID-19 survivors presenting higher rates of mental health consequences than the general population. The possible mechanisms by which the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters the brain, affecting the central nervous system (CNS) and causing these psychiatric sequelae, will be discussed, particularly concerning the SARS-CoV-2 entry via the angiotensin-converting enzyme 2 (ACE-2) receptors and the implications of the immune inflammatory signaling on neuropsychiatric disorders. Some possible therapeutic options will also be considered.

Tissue compartmentalization enables Salmonella persistence during chemotherapy

Antimicrobial chemotherapy can fail to eradicate the pathogen, even in the absence of antimicrobial resistance. Persisting pathogens can subsequently cause relapsing diseases. In vitro studies suggest various mechanisms of antibiotic persistence, but their in vivo relevance remains unclear because of the difficulty of studying scarce pathogen survivors in complex host tissues. Here, we localized and characterized rare surviving Salmonella in mouse spleen using high-resolution whole-organ tomography. Chemotherapy cleared >99.5% of the Salmonella but was inefficient against a small Salmonella subset in the white pulp. Previous models could not explain these findings: drug exposure was adequate, Salmonella continued to replicate, and host stresses induced only limited Salmonella drug tolerance. Instead, antimicrobial clearance required support of Salmonella-killing neutrophils and monocytes, and the density of such cells was lower in the white pulp than in other spleen compartments containing higher Salmonella loads. Neutrophil densities declined further during treatment in response to receding Salmonella loads, resulting in insufficient support for Salmonella clearance from the white pulp and eradication failure. However, adjunctive therapies sustaining inflammatory support enabled effective clearance. These results identify uneven Salmonella tissue colonization and spatiotemporal inflammation dynamics as main causes of Salmonella persistence and establish a powerful approach to investigate scarce but impactful pathogen subsets in complex host environments.

Evidence and Therapeutic Perspectives in the Relationship between the Oral Microbiome and Alzheimer's Disease: A Systematic Review

This review aims to clarify the nature of the link between Alzheimer’s disease and the oral microbiome on an epidemiological and pathophysiological level, as well as to highlight new therapeutic perspectives that contribute to the management of this disease. We performed a systematic review, following the Preferred Reporting Items for Systematic Reviews checklist, from January 2000 to July 2021. The terms “plaque,” “saliva,” and “mouth” were associated with the search term “oral diseases” and used in combination with the Boolean operator “AND”/“OR”. We included experimental or clinical studies and excluded conferences, abstracts, reviews, and editorials. A total of 27 articles were selected. Evidence for the impact of the oral microbiome on the pathophysiological and immunoinflammatory mechanisms of Alzheimer’s disease is accumulating. The impact of the oral microbiome on the development of AD opens the door to complementary therapies such as phototherapy and/or the use of prebiotic compounds and probiotic strains for global or targeted modulation of the oral microbiome in order to have a favourable influence on the evolution of this pathology in the future.

The Role of the Oral Microbiota in the Etiopathogenesis of Oral Squamous Cell Carcinoma

Dysbiosis in the oral environment may play a role in the etiopathogenesis of oral squamous cell carcinoma (OSCC). This review aims to summarize the current knowledge about the association of oral microbiota with OSCC and to describe possible etiopathogenetic mechanisms involved in processes of OSCC development and progression. Association studies included in this review were designed as case–control/case studies, analyzing the bacteriome, mycobiome, and virome from saliva, oral rinses, oral mucosal swabs, or oral mucosal tissue samples (deep and superficial) and comparing the results in healthy individuals to those with OSCC and/or with premalignant lesions. Changes in relative abundances of specific bacteria (e.g., Porphyromonas gingivalis, Fusobacterium nucleatum, Streptococcus sp.) and fungi (especially Candida sp.) were associated with OSCC. Viruses can also play a role; while the results of studies investigating the role of human papillomavirus in OSCC development are controversial, Epstein–Barr virus was positively correlated with OSCC. The oral microbiota has been linked to tumorigenesis through a variety of mechanisms, including the stimulation of cell proliferation, tumor invasiveness, angiogenesis, inhibition of cell apoptosis, induction of chronic inflammation, or production of oncometabolites. We also advocate for the necessity of performing a complex analysis of the microbiome in further studies and of standardizing the sampling procedures by establishing guidelines to support future meta-analyses.

SARS-CoV-2-Induced Gut Microbiome Dysbiosis: Implications for Colorectal Cancer

The emergence of a novel coronavirus, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), in December 2019 led to a worldwide pandemic with over 170 million confirmed infections and over 3.5 million deaths (as of May 2021). Early studies have shown higher mortality rates from SARS-CoV-2 infection in cancer patients than individuals without cancer. Herein, we review the evidence that the gut microbiota plays a crucial role in health and has been linked to the development of colorectal cancer (CRC). Investigations have shown that SARS-CoV-2 infection causes changes to the gut microbiota, including an overall decline in microbial diversity, enrichment of opportunistic pathogens such as Fusobacterium nucleatum bacteremia, and depletion of beneficial commensals, such as the butyrate-producing bacteria. Further, these changes lead to increased colonic inflammation, which leads to gut barrier disruption, expression of genes governing CRC tumorigenesis, and tumor immunosuppression, thus further exacerbating CRC progression. Additionally, a long-lasting impact of SARS-CoV-2 on gut dysbiosis might result in a greater possibility of new CRC diagnosis or aggravating the condition in those already afflicted. Herein, we review the evidence relating to the current understanding of how infection with SARS-CoV-2 impacts the gut microbiota and the effects this will have on CRC carcinogenesis and progression.

COVID-19 and the gastrointestinal tract: Source of infection or merely a target of the inflammatory process following SARS-CoV-2 infection?

Gastrointestinal (GI) symptoms have been described in a conspicuous percentage of coronavirus disease 2019 (COVID-19) patients. This clinical evidence is supported by the detection of viral RNA in stool, which also supports the hypothesis of a possible fecal-oral transmission route. The involvement of GI tract in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is corroborated by the theoretical assumption that angiotensin converting enzyme 2, which is a SARS-CoV-2 target receptor, is present along the GI tract. Studies have pointed out that gut dysbiosis may occur in COVID-19 patients, with a possible correlation with disease severity and with complications such as multisystem inflammatory syndrome in children. However, the question to be addressed is whether dysbiosis is a consequence or a contributing cause of SARS-CoV-2 infection. In such a scenario, pharmacological therapies aimed at decreasing GI permeability may be beneficial for COVID-19 patients. Considering the possibility of a fecal-oral transmission route, water and environmental sanitation play a crucial role for COVID-19 containment, especially in developing countries.

Antibiotic resistance: turning evolutionary principles into clinical reality

Antibiotic resistance is one of the major challenges facing modern medicine worldwide. The past few decades have witnessed rapid progress in our understanding of the multiple factors that affect the emergence and spread of antibiotic resistance at the population level and the level of the individual patient. However, the process of translating this progress into health policy and clinical practice has been slow. Here, we attempt to consolidate current knowledge about the evolution and ecology of antibiotic resistance into a roadmap for future research as well as clinical and environmental control of antibiotic resistance. At the population level, we examine emergence, transmission and dissemination of antibiotic resistance, and at the patient level, we examine adaptation involving bacterial physiology and host resilience. Finally, we describe new approaches and technologies for improving diagnosis and treatment and minimizing the spread of resistance.

Treatment timing shifts the benefits of short and long antibiotic treatment over infection

Antibiotics are the major tool for treating bacterial infections. Rising antibiotic resistance, however, calls for a better use of antibiotics. While classical recommendations favor long and aggressive treatments, more recent clinical trials advocate for moderate regimens. In this debate, two axes of 'aggression' have typically been conflated: treatment intensity (dose) and treatment duration. The third dimension of treatment timing along each individual's infection course has rarely been addressed. By using a generic mathematical model of bacterial infection controlled by immune response, we examine how the relative effectiveness of antibiotic treatment varies with its timing, duration and antibiotic kill rate. We show that short or long treatments may both be beneficial depending on treatment onset, the target criterion for success and on antibiotic efficacy. This results from the dynamic trade-off between immune response build-up and resistance risk in acute, self-limiting infections, and uncertainty relating symptoms to infection variables. We show that in our model early optimal treatments tend to be 'short and strong', while late optimal treatments tend to be 'mild and long'. This suggests a shift in the aggression axis depending on the timing of treatment. We find that any specific optimal treatment schedule may perform more poorly if evaluated by other criteria, or under different host-specific conditions. Our results suggest that major advances in antibiotic stewardship must come from a deeper empirical understanding of bacterial infection processes in individual hosts. To guide rational therapy, mathematical models need to be constrained by data, including a better quantification of personal disease trajectory in humans. Lay summary: Bacterial infections are becoming more difficult to treat worldwide because bacteria are becoming resistant to the antibiotics used. Addressing this problem requires a better understanding of how treatment along with other host factors impact antibiotic resistance. Until recently, most theoretical research has focused on the importance of antibiotic dosing on antibiotic resistance, however, duration and timing of treatment remain less explored. Here, we use a mathematical model of a generic bacterial infection to study three aspects of treatment: treatment dose/efficacy (defined by the antibiotic kill rate), duration, and timing, and their impact on several infection endpoints. We show that short and long treatment success strongly depends on when treatment begins (defined by the symptom threshold), the target criterion to optimize, and on antibiotic efficacy. We find that if administered early in an infection, "strong and short" therapy performs better, while if treatment begins at higher bacterial densities, a "mild and long" course of antibiotics is favored. In the model host immune defenses are key in preventing relapses, controlling antibiotic resistant bacteria and increasing the effectiveness of moderate intervention. In order to improve rational treatments of human infections, we call for a better quantification of individual disease trajectories in bacteria-immunity space.

A photo-sensitizable phage for multidrug-resistant Acinetobacter baumannii therapy and biofilm ablation

Antibiotic abuse causes the emergence of bacterial resistance. Photodynamic antibacterial chemotherapy (PACT) has great potential to solve serious bacterial resistance, but it suffers from the inefficient generation of ROS and the lack of bacterial targeting ability. Herein, a unique cationic photosensitizer (NB) and bacteriophage (ABP)-based photodynamic antimicrobial agent (APNB) is developed for precise bacterial eradication and efficient biofilm ablation. Thanks to the structural modification of the NB photosensitizer with a sulfur atom, it displays excellent reactive oxygen species (ROS)-production ability. Moreover, specific binding to pathogenic microorganisms can be provided by bacteriophages. The developed APNB has multiple functions, including bacteria targeting, near-infrared fluorescence imaging and combination therapy (PACT and phage therapy). Both in vitro and in vivo experiments prove that APNB can efficiently treat A. baumannii infection. Particularly, the recovery from A. baumannii infection after APNB treatment is faster than that with ampicillin and polymyxin B in vivo. Furthermore, the strategy of combining bacteriophages and photosensitizers is employed to eradicate bacterial biofilms for the first time, and it shows the excellent biofilm ablation effect as expected. Thus, APNB has huge potential in fighting against multidrug-resistant bacteria and biofilm ablation in practice.

APNB for multidrug-resistant A. Baumannii therapy and biofilms ablation.

Antibiotic Resistance: Moving From Individual Health Norms to Social Norms in One Health and Global Health

Antibiotic resistance is a problem for human health, and consequently, its study had been traditionally focused toward its impact for the success of treating human infections in individual patients (individual health). Nevertheless, antibiotic-resistant bacteria and antibiotic resistance genes are not confined only to the infected patients. It is now generally accepted that the problem goes beyond humans, hospitals, or long-term facility settings and that it should be considered simultaneously in human-connected animals, farms, food, water, and natural ecosystems. In this regard, the health of humans, animals, and local antibiotic-resistance-polluted environments should influence the health of the whole interconnected local ecosystem (One Health). In addition, antibiotic resistance is also a global problem; any resistant microorganism (and its antibiotic resistance genes) could be distributed worldwide. Consequently, antibiotic resistance is a pandemic that requires Global Health solutions. Social norms, imposing individual and group behavior that favor global human health and in accordance with the increasingly collective awareness of the lack of human alienation from nature, will positively influence these solutions. In this regard, the problem of antibiotic resistance should be understood within the framework of socioeconomic and ecological efforts to ensure the sustainability of human development and the associated human-natural ecosystem interactions.

Human antimicrobial peptide, LL-37, induces non-inheritable reduced susceptibility to vancomycin in Staphylococcus aureus

Antimicrobial peptides (AMPs) are central components of the innate immune system providing protection against pathogens. Yet, serum and tissue concentrations vary between individuals and with disease conditions. We demonstrate that the human AMP LL-37 lowers the susceptibility to vancomycin in the community-associated methicillin-resistant S. aureus (CA-MRSA) strain FPR3757 (USA300). Vancomycin is used to treat serious MRSA infections, but treatment failures occur despite MRSA strains being tested susceptible according to standard susceptibility methods. Exposure to physiologically relevant concentrations of LL-37 increased the minimum inhibitory concentration (MIC) of S. aureus towards vancomycin by 75%, and resulted in shortened lag-phase and increased colony formation at sub-inhibitory concentrations of vancomycin. Computer simulations using a mathematical antibiotic treatment model indicated that a small increase in MIC might decrease the efficacy of vancomycin in clearing a S. aureus infection. This prediction was supported in a Galleria mellonella infection model, where exposure of S. aureus to LL-37 abolished the antimicrobial effect of vancomycin. Thus, physiological relevant concentrations of LL-37 reduce susceptibility to vancomycin, indicating that tissue and host specific variations in LL-37 concentrations may influence vancomycin susceptibility in vivo.

Effect of drug dose and timing of treatment on the emergence of drug resistance in vivo in a malaria model

BACKGROUND AND OBJECTIVES

There is a significant interest in identifying clinically effective drug treatment regimens that minimize the de novo evolution of antimicrobial resistance in pathogen populations. However, in vivo studies that vary treatment regimens and directly measure drug resistance evolution are rare. Here, we experimentally investigate the role of drug dose and treatment timing on resistance evolution in an animal model.

METHODOLOGY

In a series of experiments, we measured the emergence of atovaquone-resistant mutants of Plasmodium chabaudi in laboratory mice, as a function of dose or timing of treatment (day post-infection) with the antimalarial drug atovaquone.

RESULTS

The likelihood of high-level resistance emergence increased with atovaquone dose. When varying the timing of treatment, treating either very early or late in infection reduced the risk of resistance. When we varied starting inoculum, resistance was more likely at intermediate inoculum sizes, which correlated with the largest population sizes at time of treatment.

CONCLUSIONS AND IMPLICATIONS

(i) Higher doses do not always minimize resistance emergence and can promote the emergence of high-level resistance. (ii) Altering treatment timing affects the risk of resistance emergence, likely due to the size of the population at the time of treatment, although we did not test the effect of immunity whose influence may have been important in the case of late treatment. (iii) Finding the 'right' dose and 'right' time to maximize clinical gains and limit resistance emergence can vary depending on biological context and was non-trivial even in our simplified experiments.

LAY SUMMARY

In a mouse model of malaria, higher drug doses led to increases in drug resistance. The timing of drug treatment also impacted resistance emergence, likely due to the size of the population at the time of treatment.

Fe3O4@TiO2-Laden Neutrophils Activate Innate Immunity via Photosensitive Reactive Oxygen Species Release

Although a variety of advanced sterilization materials and treatments have emerged, the complete elimination of bacterial infection, especially drug-resistant bacterial infection, remains an immense challenge. Here, we demonstrate the use of neutrophils loaded with photocatalytic nanoparticles to reduce bacterial infection. This method activates the immune system to achieve an anti-infection response. We prepared the photocatalytic nanoparticle-laden neutrophils in vivo through neutrophil phagocytosis. The resulting loaded cells retained the cell membrane functionality of the source cell, as well as the complete immune cell function of neutrophils, particularly the ability to recruit macrophages to the target area. Photocatalytic nanoparticle-laden neutrophils can target infection sites and release reactive oxygen species to induce the secretion of chemokines, leading to the targeted recruitment of macrophages and enhancing a powerful immune cascade. In a severe mouse infection model induced by pathogenic bacteria, small doses of photocatalytic nanoparticle-laden neutrophils showed a remarkable therapeutic effect by enhancing macrophage recruitment and the immune cascade.

Antibiotic chemotherapy against heterogeneous pathogen populations in complex host tissues

Antibiotic chemotherapy effectively cures many infections caused by susceptible bacterial pathogens. However, in some cases, even extended treatment duration does not completely eradicate the pathogenic bacteria from host tissues. A common model for underlying mechanisms assumes the stochastic formation of bacterial persisters similar to observations in laboratory cultures. However, alternative explanations related to the complexity of infected host tissues could also be relevant. We discuss several of these aspects and emphasize the need for integrated analysis as a basis for new control strategies.

Aggressive or moderate drug therapy for infectious diseases? Trade-offs between different treatment goals at the individual and population levels

Antimicrobial resistance is one of the major public health threats of the 21st century. There is a pressing need to adopt more efficient treatment strategies in order to prevent the emergence and spread of resistant strains. The common approach is to treat patients with high drug doses, both to clear the infection quickly and to reduce the risk of de novo resistance. Recently, several studies have argued that, at least in some cases, low-dose treatments could be more suitable to reduce the within-host emergence of antimicrobial resistance. However, the choice of a drug dose may have consequences at the population level, which has received little attention so far. Here, we study the influence of the drug dose on resistance and disease management at the host and population levels. We develop a nested two-strain model and unravel trade-offs in treatment benefits between an individual and the community. We use several measures to evaluate the benefits of any dose choice. Two measures focus on the emergence of resistance, at the host level and at the population level. The other two focus on the overall treatment success: the outbreak probability and the disease burden. We find that different measures can suggest different dosing strategies. In particular, we identify situations where low doses minimize the risk of emergence of resistance at the individual level, while high or intermediate doses prove most beneficial to improve the treatment efficiency or even to reduce the risk of resistance in the population.

Antibiotic Killing of Diversely Generated Populations of Nonreplicating Bacteria

Nonreplicating bacteria are known to be (or at least commonly thought to be) refractory to antibiotics to which they are genetically susceptible. Here, we explore the sensitivity to killing by bactericidal antibiotics of three classes of nonreplicating populations of planktonic bacteria: (i) stationary phase, when the concentration of resources and/or nutrients are too low to allow for population growth; (ii) persisters, minority subpopulations of susceptible bacteria surviving exposure to bactericidal antibiotics; and (iii) antibiotic-static cells, bacteria exposed to antibiotics that prevent their replication but kill them slowly if at all, the so-called bacteriostatic drugs. Using experimental populations of Staphylococcus aureus Newman and Escherichia coli K-12 (MG1655) and, respectively, nine and seven different bactericidal antibiotics, we estimated the rates at which these drugs kill these different types of nonreplicating bacteria. In contrast to the common belief that bacteria that are nonreplicating are refractory to antibiotic-mediated killing, all three types of nonreplicating populations of these Gram-positive and Gram-negative bacteria are consistently killed by aminoglycosides and the peptide antibiotics daptomycin and colistin, respectively. This result indicates that nonreplicating cells, irrespectively of why they do not replicate, have an almost identical response to bactericidal antibiotics. We discuss the implications of these results to our understanding of the mechanisms of action of antibiotics and the possibility of adding a short-course of aminoglycosides or peptide antibiotics to conventional therapy of bacterial infections.

Computational Health Engineering Applied to Model Infectious Diseases and Antimicrobial Resistance Spread

Infectious diseases are the primary cause of mortality worldwide. The dangers of infectious disease are compounded with antimicrobial resistance, which remains the greatest concern for human health. Although novel approaches are under investigation, the World Health Organization predicts that by 2050, septicaemia caused by antimicrobial resistant bacteria could result in 10 million deaths per year. One of the main challenges in medical microbiology is to develop novel experimental approaches, which enable a better understanding of bacterial infections and antimicrobial resistance. After the introduction of whole genome sequencing, there was a great improvement in bacterial detection and identification, which also enabled the characterization of virulence factors and antimicrobial resistance genes. Today, the use of in silico experiments jointly with computational and machine learning offer an in depth understanding of systems biology, allowing us to use this knowledge for the prevention, prediction, and control of infectious disease. Herein, the aim of this review is to discuss the latest advances in human health engineering and their applicability in the control of infectious diseases. An in-depth knowledge of host–pathogen–protein interactions, combined with a better understanding of a host’s immune response and bacterial fitness, are key determinants for halting infectious diseases and antimicrobial resistance dissemination.

The high prevalence of antibiotic heteroresistance in pathogenic bacteria is mainly caused by gene amplification

When choosing antibiotics to treat bacterial infections, it is assumed that the susceptibility of the target bacteria to an antibiotic is reflected by laboratory estimates of the minimum inhibitory concentration (MIC) needed to prevent bacterial growth. A caveat of using MIC data for this purpose is heteroresistance, the presence of a resistant subpopulation in a main population of susceptible cells. We investigated the prevalence and mechanisms of heteroresistance in 41 clinical isolates of the pathogens Escherichia coli, Salmonella enterica, Klebsiella pneumoniae and Acinetobacter baumannii against 28 different antibiotics. For the 766 bacteria-antibiotic combinations tested, as much as 27.4% of the total was heteroresistant. Genetic analysis demonstrated that a majority of heteroresistance cases were unstable, with an increased resistance of the subpopulations resulting from spontaneous tandem amplifications, typically including known resistance genes. Using mathematical modelling, we show how heteroresistance in the parameter range estimated in this study can result in the failure of antibiotic treatment of infections with bacteria that are classified as antibiotic susceptible. The high prevalence of heteroresistance with the potential for treatment failure highlights the limitations of MIC as the sole criterion for susceptibility determinations. These results call for the development of facile and rapid protocols to identify heteroresistance in pathogens.

Simulating Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model

Membrane computing is a bio-inspired computing paradigm whose devices are the so-called membrane systems or P systems. The P system designed in this work reproduces complex biological landscapes in the computer world. It uses nested "membrane-surrounded entities" able to divide, propagate, and die; to be transferred into other membranes; to exchange informative material according to flexible rules; and to mutate and be selected by external agents. This allows the exploration of hierarchical interactive dynamics resulting from the probabilistic interaction of genes (phenotypes), clones, species, hosts, environments, and antibiotic challenges. Our model facilitates analysis of several aspects of the rules that govern the multilevel evolutionary biology of antibiotic resistance. We examined a number of selected landscapes where we predict the effects of different rates of patient flow from hospital to the community and vice versa, the cross-transmission rates between patients with bacterial propagules of different sizes, the proportion of patients treated with antibiotics, and the antibiotics and dosing found in the opening spaces in the microbiota where resistant phenotypes multiply. We also evaluated the selective strengths of some drugs and the influence of the time 0 resistance composition of the species and bacterial clones in the evolution of resistance phenotypes. In summary, we provide case studies analyzing the hierarchical dynamics of antibiotic resistance using a novel computing model with reciprocity within and between levels of biological organization, a type of approach that may be expanded in the multilevel analysis of complex microbial landscapes.IMPORTANCE The work that we present here represents the culmination of many years of investigation in looking for a suitable methodology to simulate the multihierarchical processes involved in antibiotic resistance. Everything started with our early appreciation of the different independent but embedded biological units that shape the biology, ecology, and evolution of antibiotic-resistant microorganisms. Genes, plasmids carrying these genes, cells hosting plasmids, populations of cells, microbial communities, and host's populations constitute a complex system where changes in one component might influence the other ones. How would it be possible to simulate such a complexity of antibiotic resistance as it occurs in the real world? Can the process be predicted, at least at the local level? A few years ago, and because of their structural resemblance to biological systems, we realized that membrane computing procedures could provide a suitable frame to approach these questions. Our manuscript describes the first application of this modeling methodology to the field of antibiotic resistance and offers a bunch of examples-just a limited number of them in comparison with the possible ones to illustrate its unprecedented explanatory power.

Bacterial persistence promotes the evolution of antibiotic resistance by increasing survival and mutation rates

Persisters are transiently antibiotic-tolerant cells that complicate the treatment of bacterial infections. Both theory and experiments have suggested that persisters facilitate genetic resistance by constituting an evolutionary reservoir of viable cells. Here, we provide evidence for a strong positive correlation between persistence and the likelihood to become genetically resistant in natural and lab strains of E. coli. This correlation can be partly attributed to the increased availability of viable cells associated with persistence. However, our data additionally show that persistence is pleiotropically linked with mutation rates. Our theoretical model further demonstrates that increased survival and mutation rates jointly affect the likelihood of evolving clinical resistance. Overall, these results suggest that the battle against antibiotic resistance will benefit from incorporating anti-persister therapies.

Emergence and selection of isoniazid and rifampin resistance in tuberculosis granulomas

Drug resistant tuberculosis is increasing world-wide. Resistance against isoniazid (INH), rifampicin (RIF), or both (multi-drug resistant TB, MDR-TB) is of particular concern, since INH and RIF form part of the standard regimen for TB disease. While it is known that suboptimal treatment can lead to resistance, it remains unclear how host immune responses and antibiotic dynamics within granulomas (sites of infection) affect emergence and selection of drug-resistant bacteria. We take a systems pharmacology approach to explore resistance dynamics within granulomas. We integrate spatio-temporal host immunity, INH and RIF dynamics, and bacterial dynamics (including fitness costs and compensatory mutations) in a computational framework. We simulate resistance emergence in the absence of treatment, as well as resistance selection during INH and/or RIF treatment. There are four main findings. First, in the absence of treatment, the percentage of granulomas containing resistant bacteria mirrors the non-monotonic bacterial dynamics within granulomas. Second, drug-resistant bacteria are less frequently found in non-replicating states in caseum, compared to drug-sensitive bacteria. Third, due to a steeper dose response curve and faster plasma clearance of INH compared to RIF, INH-resistant bacteria have a stronger influence on treatment outcomes than RIF-resistant bacteria. Finally, under combination therapy with INH and RIF, few MDR bacteria are able to significantly affect treatment outcomes. Overall, our approach allows drug-specific prediction of drug resistance emergence and selection in the complex granuloma context. Since our predictions are based on pre-clinical data, our approach can be implemented relatively early in the treatment development process, thereby enabling pro-active rather than reactive responses to emerging drug resistance for new drugs. Furthermore, this quantitative and drug-specific approach can help identify drug-specific properties that influence resistance and use this information to design treatment regimens that minimize resistance selection and expand the useful life-span of new antibiotics.

Alternative therapeutics for self-limiting infections-An indirect approach to the antibiotic resistance challenge

Alternative therapeutics for infectious diseases is a top priority, but what infections should be the primary targets? At present there is a focus on therapies for severe infections, for which effective treatment is most needed, but these infections are hard to manage, and progress has been limited. Here, we explore a different approach. Applying an evolutionary perspective to a review of antibiotic prescription studies, we identify infections that likely make a large contribution to resistance evolution across multiple taxa but are clinically mild and thus present easier targets for therapeutics development. Alternative therapeutics for these infections, we argue, would save lives indirectly by preserving the high efficacy of existing antibiotics for the patients who need them the most.