C-di-AMP levels modulate Staphylococcus aureus cell wall thickness, response to oxidative stress, and antibiotic resistance and tolerance.

IMPORTANCE: Antibiotic resistance and tolerance are substantial healthcare-related problems, hampering effective treatment of bacterial infections. Mutations in the phosphodiesterase GdpP, which degrades cyclic di-3', 5'-adenosine monophosphate (c-di-AMP), have recently been associated with resistance to beta-lactam antibiotics in clinical Staphylococcus aureus isolates. In this study, we show that high c-di-AMP levels decreased the cell size and increased the cell wall thickness in S. aureus mutant strains. As a consequence, an increase in resistance to cell wall targeting antibiotics, such as oxacillin and fosfomycin as well as in tolerance to ceftaroline, a cephalosporine used to treat methicillin-resistant S. aureus infections, was observed. These findings underline the importance of investigating the role of c-di-AMP in the development of tolerance and resistance to antibiotics in order to optimize treatment in the clinical setting.

Antibacterial Neutrophil Effector Response: Ex Vivo Quantification of Regulated Cell Death Associated with Extracellular Trap Release.

Regulated cell death (RCD) and the concomitant release of extracellular traps by neutrophils (NETs) constitute an important antibacterial effector response. Usually, the dynamic processes of RCD and NETs release are assessed independently of each other by either unspecific or time-consuming methods. Here, we describe a flow cytometry-based high-throughput analysis method incorporating neutrophil RCD and NETs release with visual live-imaging conformation upon ex vivo bacterial challenge. This combined approach allows to quantify and closely follow the kinetics of the dynamic neutrophil effector response towards bacterial infection.

Serine-threonine phosphoregulation by PknB and Stp contributes to quiescence and antibiotic tolerance in Staphylococcus aureus.

Staphylococcus aureus can cause infections that are often chronic and difficult to treat, even when the bacteria are not antibiotic resistant because most antibiotics act only on metabolically active cells. Subpopulations of persister cells are metabolically quiescent, a state associated with delayed growth, reduced protein synthesis, and increased tolerance to antibiotics. Serine-threonine kinases and phosphatases similar to those found in eukaryotes can fine-tune essential bacterial cellular processes, such as metabolism and stress signaling. We found that acid stress-mimicking conditions that S. aureus experiences in host tissues delayed growth, globally altered the serine and threonine phosphoproteome, and increased threonine phosphorylation of the activation loop of the serine-threonine protein kinase B (PknB). The deletion of stp, which encodes the only annotated functional serine-threonine phosphatase in S. aureus, increased the growth delay and phenotypic heterogeneity under different stress challenges, including growth in acidic conditions, the intracellular milieu of human cells, and abscesses in mice. This growth delay was associated with reduced protein translation and intracellular ATP concentrations and increased antibiotic tolerance. Using phosphopeptide enrichment and mass spectrometry-based proteomics, we identified targets of serine-threonine phosphorylation that may regulate bacterial growth and metabolism. Together, our findings highlight the importance of phosphoregulation in mediating bacterial quiescence and antibiotic tolerance and suggest that targeting PknB or Stp might offer a future therapeutic strategy to prevent persister formation during S. aureus infections.

Quantification of within-patient Staphylococcus aureus phenotypic heterogeneity as a proxy for the presence of persisters across clinical presentations.

OBJECTIVES: Difficult-to-treat infections caused by antibiotic-susceptible strains have been linked to the occurrence of persisters, a subpopulation of dormant bacteria that tolerate antibiotic exposure despite lacking genetic resistance. These persisters can be identified phenotypically by plating on nutrient agar because of their altered growth dynamics, resulting in colony-size heterogeneity. The occurrence of within-patient bacterial phenotypic heterogeneity in various infections and clinical determinants of persister formation remains unknown. METHODS: We plated bacteria derived from 132 patient samples of difficult-to-treat infections directly on nutrient-rich agar and monitored colony growth by time-lapse imaging. We retained 36 Staphylococcus aureus monocultures for further analysis. We investigated clinical factors associated with increased colony growth-delay with regression analyses. We corroborated the clinical findings using in vitro grown static biofilms exposed to distinct antibiotics. RESULTS: The extent of phenotypic heterogeneity of patient-derived S. aureus varied substantially between patients (from no delay to a maximum of 57.6 hours). Increased heterogeneity coincided with increased median colony growth-delay. Multivariable regression showed that rifampicin treatment was significantly associated with increased median growth-delay (13.3 hours; 95% CI 7.13-19.6 hours; p < 0.001). S. aureus grown in biofilms and exposed to high concentrations of rifampicin or a combination of rifampicin with clindamycin or levofloxacin exhibited prolonged growth-delay (p < 0.05 for 11 of 12 comparisons), correlating with a strain-dependent increase in antibiotic tolerance. DISCUSSION: Colony-size heterogeneity upon direct sampling of difficult-to-treat S. aureus infections was frequently observed. Hence, future studies are needed to assess the potential benefit of phenotypic heterogeneity quantification for staphylococcal infection prognosis and treatment guidelines.

Hyperinflammatory environment drives dysfunctional myeloid cell effector response to bacterial challenge in COVID-19.

COVID-19 displays diverse disease severities and symptoms including acute systemic inflammation and hypercytokinemia, with subsequent dysregulation of immune cells. Bacterial superinfections in COVID-19 can further complicate the disease course and are associated with increased mortality. However, there is limited understanding of how SARS-CoV-2 pathogenesis and hypercytokinemia impede the innate immune function against bacterial superinfections. We assessed the influence of COVID-19 plasma hypercytokinemia on the functional responses of myeloid immune cells upon bacterial challenges from acute-phase COVID-19 patients and their corresponding recovery-phase. We show that a severe hypercytokinemia status in COVID-19 patients correlates with the development of bacterial superinfections. Neutrophils and monocytes derived from COVID-19 patients in their acute-phase showed an impaired intracellular microbicidal capacity upon bacterial challenges. The impaired microbicidal capacity was reflected by abrogated MPO and reduced NETs production in neutrophils along with reduced ROS production in both neutrophils and monocytes. Moreover, we observed a distinct pattern of cell surface receptor expression on both neutrophils and monocytes, in line with suppressed autocrine and paracrine cytokine signaling. This phenotype was characterized by a high expression of CD66b, CXCR4 and low expression of CXCR1, CXCR2 and CD15 in neutrophils and low expression of HLA-DR, CD86 and high expression of CD163 and CD11b in monocytes. Furthermore, the impaired antibacterial effector function was mediated by synergistic effect of the cytokines TNF-α, IFN-γ and IL-4. COVID-19 patients receiving dexamethasone showed a significant reduction of overall inflammatory markers in the plasma as well as exhibited an enhanced immune response towards bacterial challenge ex vivo. Finally, broad anti-inflammatory treatment was associated with a reduction in CRP, IL-6 levels as well as length of ICU stay and ventilation-days in critically ill COVID-19 patients. Our data provides insights into the transient functional dysregulation of myeloid immune cells against subsequent bacterial infections in COVID-19 patients and describe a beneficial role for the use of dexamethasone in these patients.

Blunted sFasL signalling exacerbates TNF-driven neutrophil necroptosis in critically ill COVID-19 patients.

OBJECTIVES: Critically ill coronavirus disease 2019 (COVID-19) patients are characterised by a severely dysregulated cytokine profile and elevated neutrophil counts, impacting disease severity. However, it remains unclear how neutrophils contribute to pathophysiology during COVID-19. Here, we assessed the impact of the dysregulated cytokine profile on the regulated cell death (RCD) programme of neutrophils. METHODS: Regulated cell death phenotype of neutrophils isolated from critically ill COVID-19 patients or healthy donors and stimulated with COVID-19 or healthy plasma ex vivo was assessed by flow cytometry, time-lapse microscopy and cytokine multiplex analysis. Immunohistochemistry of COVID-19 patients and control biopsies were performed to assess the in situ neutrophil RCD phenotype. Plasma cytokine levels of COVID-19 patients and healthy donors were measured by multiplex analysis. Clinical parameters were correlated to cytokine levels of COVID-19 patients. RESULTS: COVID-19 plasma induced a necroptosis-sensitive neutrophil phenotype, characterised by cell lysis, elevated release of damage-associated molecular patterns (DAMPs), increased receptor-interacting serine/threonine-protein kinase (RIPK) 1 levels and mixed lineage kinase domain-like pseudokinase (MLKL) involvement. The occurrence of neutrophil necroptosis MLKL axis was further confirmed in COVID-19 thrombus and lung biopsies. Necroptosis was induced by the tumor necrosis factor receptor 1 (TNFRI)/TNF-α axis. Moreover, reduction of soluble Fas ligand (sFasL) levels in COVID-19 patients and hence decreased signalling to Fas directly increased RIPK1 levels, exacerbated TNF-driven necroptosis and correlated with disease severity, which was abolished in patients treated with glucocorticoids. CONCLUSION: Our results suggest a novel role for sFasL signalling in the TNF-α-induced RCD programme in neutrophils during COVID-19 and a potential therapeutic target to curb inflammation and thus influence disease severity and outcome.

Molecular reprogramming and phenotype switching in Staphylococcus aureus lead to high antibiotic persistence and affect therapy success.

Staphylococcus aureus causes invasive infections and easily acquires antibiotic resistance. Even antibiotic-susceptible S. aureus can survive antibiotic therapy and persist, requiring prolonged treatment and surgical interventions. These so-called persisters display an arrested-growth phenotype, tolerate high antibiotic concentrations, and are associated with chronic and recurrent infections. To characterize these persisters, we assessed S. aureus recovered directly from a patient suffering from a persistent infection. We show that host-mediated stress, including acidic pH, abscess environment, and antibiotic exposure promoted persister formation in vitro and in vivo. Multiomics analysis identified molecular changes in S. aureus in response to acid stress leading to an overall virulent population. However, further analysis of a persister-enriched population revealed major molecular reprogramming in persisters, including down-regulation of virulence and cell division and up-regulation of ribosomal proteins, nucleotide-, and amino acid-metabolic pathways, suggesting their requirement to fuel and maintain the persister phenotype and highlighting that persisters are not completely metabolically inactive. Additionally, decreased aconitase activity and ATP levels and accumulation of insoluble proteins involved in transcription, translation, and energy production correlated with persistence in S. aureus, underpinning the molecular mechanisms that drive the persister phenotype. Upon regrowth, these persisters regained their virulence potential and metabolically active phenotype, including reduction of insoluble proteins, exhibiting a reversible state, crucial for recurrent infections. We further show that a targeted antipersister combination therapy using retinoid derivatives and antibiotics significantly reduced lag-phase heterogeneity and persisters in a murine infection model. Our results provide molecular insights into persisters and help explain why persistent S. aureus infections are so difficult to treat.

Efficient microbial colony growth dynamics quantification with ColTapp, an automated image analysis application.

Populations of genetically identical bacteria are phenotypically heterogeneous, giving rise to population functionalities that would not be possible in homogeneous populations. For instance, a proportion of non-dividing bacteria could persist through antibiotic challenges and secure population survival. This heterogeneity can be studied in complex environmental or clinical samples by spreading the bacteria on agar plates and monitoring time to growth resumption in order to infer their metabolic state distribution. We present ColTapp, the Colony Time-lapse application for bacterial colony growth quantification. Its intuitive graphical user interface allows users to analyze time-lapse images of agar plates to monitor size, color and morphology of colonies. Additionally, images at isolated timepoints can be used to estimate lag time. Using ColTapp, we analyze a dataset of Staphylococcus aureus time-lapse images including populations with heterogeneous lag time. Colonies on dense plates reach saturation early, leading to overestimation of lag time from isolated images. We show that this bias can be corrected by taking into account the area available to each colony on the plate. We envision that in clinical settings, improved analysis of colony growth dynamics may help treatment decisions oriented towards personalized antibiotic therapies.

Wide lag time distributions break a trade-off between reproduction and survival in bacteria.

Many microorganisms face a fundamental trade-off between reproduction and survival: Rapid growth boosts population size but makes microorganisms sensitive to external stressors. Here, we show that starved bacteria encountering new resources can break this trade-off by evolving phenotypic heterogeneity in lag time. We quantify the distribution of single-cell lag times of populations of starved Escherichia coli and show that population growth after starvation is primarily determined by the cells with shortest lag due to the exponential nature of bacterial population dynamics. As a consequence, cells with long lag times have no substantial effect on population growth resumption. However, we observe that these cells provide tolerance to stressors such as antibiotics. This allows an isogenic population to break the trade-off between reproduction and survival. We support this argument with an evolutionary model which shows that bacteria evolve wide lag time distributions when both rapid growth resumption and survival under stressful conditions are under selection. Our results can explain the prevalence of antibiotic tolerance by lag and demonstrate that the benefits of phenotypic heterogeneity in fluctuating environments are particularly high when minorities with extreme phenotypes dominate population dynamics.

Observing Nutrient Gradients, Gene Expression and Growth Variation Using the "Yeast Machine" Microfluidic Device.

The natural environment of microbial cells like bacteria and yeast is often a complex community in which growth and internal organization reflect morphogenetic processes and interactions that are dependent on spatial position and time. While most of research is performed in simple homogeneous environments (e.g., bulk liquid cultures), which cannot capture full spatiotemporal community dynamics, studying biofilms or colonies is complex and usually does not give access to the spatiotemporal dynamics at single cell level. Here, we detail a protocol for generation of a microfluidic device, the "yeast machine", with arrays of long monolayers of yeast colonies to advance the global understanding of how intercellular metabolic interactions affect the internal structure of colonies within defined and customizable spatial dimensions. With Saccharomyces cerevisiae as a model yeast system we used the "yeast machine" to demonstrate the emergence of glucose gradients by following expression of fluorescently labelled hexose transporters. We further quantified the expression spatial patterns with intra-colony growth rates and expression of other genes regulated by glucose availability. In addition to this, we showed that gradients of amino acids also form within a colony, potentially opening similar approaches to study spatiotemporal formation of gradients of many other nutrients and metabolic waste products. This approach could be used in the future to decipher the interplay between long-range metabolic interactions, cellular development, and morphogenesis in other same species or more complex multi-species systems at single-cell resolution and timescales relevant to ecology and evolution.

A microfluidic device for inferring metabolic landscapes in yeast monolayer colonies.

Microbial colonies are fascinating structures in which growth and internal organization reflect complex morphogenetic processes. Here, we generated a microfluidics device with arrays of long monolayer yeast colonies to further global understanding of how intercellular metabolic interactions affect the internal structure of colonies within defined boundary conditions. We observed the emergence of stable glucose gradients using fluorescently labeled hexose transporters and quantified the spatial correlations with intra-colony growth rates and expression of other genes regulated by glucose availability. These landscapes depended on the external glucose concentration as well as secondary gradients, for example amino acid availability. This work demonstrates the regulatory genetic networks governing cellular physiological adaptation are the key to internal structuration of cellular assemblies. This approach could be used in the future to decipher the interplay between long-range metabolic interactions, cellular development and morphogenesis in more complex systems.

In-host evolution of Staphylococcus epidermidis in a pacemaker-associated endocarditis resulting in increased antibiotic tolerance.

Treatment failure in biofilm-associated bacterial infections is an important healthcare issue. In vitro studies and mouse models suggest that bacteria enter a slow-growing/non-growing state that results in transient tolerance to antibiotics in the absence of a specific resistance mechanism. However, little clinical confirmation of antibiotic tolerant bacteria in patients exists. In this study we investigate a Staphylococcus epidermidis pacemaker-associated endocarditis, in a patient who developed a break-through bacteremia despite taking antibiotics to which the S. epidermidis isolate is fully susceptible in vitro. Characterization of the clinical S. epidermidis isolates reveals in-host evolution over the 16-week infection period, resulting in increased antibiotic tolerance of the entire population due to a prolonged lag time until growth resumption and a reduced growth rate. Furthermore, we observe adaptation towards an increased biofilm formation capacity and genetic diversification of the S. epidermidis isolates within the patient.

The rate of environmental fluctuations shapes ecological dynamics in a two-species microbial system.

Species interactions change when the external conditions change. How these changes affect microbial community properties is an open question. We address this question using a two-species consortium in which species interactions change from exploitation to competition depending on the carbon source provided. We built a mathematical model and calibrated it using single-species growth measurements. This model predicted that low frequencies of change between carbon sources lead to species loss, while intermediate and high frequencies of change maintained both species. We experimentally confirmed these predictions by growing co-cultures in fluctuating environments. These findings complement more established concepts of a diversity peak at intermediate disturbance frequencies. They also provide a mechanistic understanding for how the dynamics at the community level emerges from single-species behaviours and interspecific interactions. Our findings suggest that changes in species interactions can profoundly impact the ecological dynamics and properties of microbial systems.

Prolonged bacterial lag time results in small colony variants that represent a sub-population of persisters.

Persisters are a subpopulation of bacteria that are not killed by antibiotics even though they lack genetic resistance. Here we provide evidence that persisters can manifest as small colony variants (SCVs) in clinical infections. We analyze growth kinetics of Staphylococcus aureus sampled from in vivo conditions and in vitro stress conditions that mimic growth in host compartments. We report that SCVs arise as a result of a long lag time, and that this phenotype emerges de novo during the growth phase in various stress conditions including abscesses and acidic media. We further observe that long lag time correlates with antibiotic usage. These observations suggest that treatment strategies should be carefully tailored to address bacterial persisters in clinics.

Identification of individual cells from z-stacks of bright-field microscopy images.

Obtaining single cell data from time-lapse microscopy images is critical for quantitative biology, but bottlenecks in cell identification and segmentation must be overcome. We propose a novel, versatile method that uses machine learning classifiers to identify cell morphologies from z-stack bright-field microscopy images. We show that axial information is enough to successfully classify the pixels of an image, without the need to consider in focus morphological features. This fast, robust method can be used to identify different cell morphologies, including the features of E. coli, S. cerevisiae and epithelial cells, even in mixed cultures. Our method demonstrates the potential of acquiring and processing Z-stacks for single-layer, single-cell imaging and segmentation.

Growing yeast into cylindrical colonies.

Microorganisms often form complex multicellular assemblies such as biofilms and colonies. Understanding the interplay between assembly expansion, metabolic yield, and nutrient diffusion within a freely growing colony remains a challenge. Most available data on microorganisms are from planktonic cultures, due to the lack of experimental tools to control the growth of multicellular assemblies. Here, we propose a method to constrain the growth of yeast colonies into simple geometric shapes such as cylinders. To this end, we designed a simple, versatile culture system to control the location of nutrient delivery below a growing colony. Under such culture conditions, yeast colonies grow vertically and only at the locations where nutrients are delivered. Colonies increase in height at a steady growth rate that is inversely proportional to the cylinder radius. We show that the vertical growth rate of cylindrical colonies is not defined by the single-cell division rate, but rather by the colony metabolic yield. This contrasts with cells in liquid culture, in which the single-cell division rate is the only parameter that defines the population growth rate. This method also provides a direct, simple method to estimate the metabolic yield of a colony. Our study further demonstrates the importance of the shape of colonies on setting their expansion. We anticipate that our approach will be a starting point for elaborate studies of the population dynamics, evolution, and ecology of microbial colonies in complex landscapes.

Micropatterned porous membranes for combinatorial cell-based assays.

Here, we describe a protocol for producing micropatterned porous membranes which can be used for combinatorial cell-based assays. We use contact printing to pattern the surface of a porous filter membrane with a thin layer of polydimethylsiloxane (PDMS). This allows the porosity of the filter membrane to be altered at selected locations. Cells can be grown on one side of the filter membrane, while drugs and reagents can be deposited on the porous areas of the other side of the membrane. The reagents can diffuse through the pores of the membrane to the cells. The first part of the protocol describes how to design a stamp and use it to contact print PDMS. The second part describes how to create microprinted membranes for cell-based assays. The method is simple, highly customizable, can be performed at the bench, and can be used to perform combinatorial or time-dependent cell-based assays.