Biology subjects

Krachler, A. M.

Publications and source records attributed to Krachler, A. M..

5 recordsLinked to original sources

bioRxiv2026

Surface sensing and metabolic signals drive feedback regulation of long polar fimbriae in enterohemorrhagic Escherichia coli O157

Bacterial colonization requires coordinated regulation of adhesion structures in response to environmental conditions. While metabolic regulation of adhesin expression is well established, how surface sensing contributes to this regulation remains less understood. Here, we investigated the regulation and function of long polar fimbriae (Lpf) in enterohemorrhagic Escherichia coli O157. We show that the lpf1 and lpf2 promoters integrate metabolic and surface-associated signals through distinct regulatory regions. Bile induces both promoters independently of distal regulatory sequences, whereas these regions repress basal transcription and are required for induction following surface association. Surface-dependent activation of both lpf promoters is reduced in mutants lacking the major fimbrial subunits LpfA1 and LpfA2, but is unaffected by deletion of the distal tip adhesins. Lpf structures also promote surface-dependent activation of ler, a positive regulator of lpf expression, supporting a regulatory feedback circuit linking surface sensing to lpf transcription. Loss of the major fimbrial subunits also impairs colonization in zebrafish, whereas deletion of the tip adhesins does not under the conditions tested. Together, these findings show that Lpf integrate environmental signals through surface-dependent regulatory feedback and identify an additional role for the fimbrial structure during colonization that does not require the tip adhesins.

microbiology↗

bioRxiv2023

Colonization of larval zebrafish (Danio rerio) with adherent-invasive Escherichia coli prevents recovery of the intestinal mucosa from drug-induced colitis

Inflammatory bowel disease (IBD) is a broad term for a range of chronic intestinal disorders, including Crohns disease and ulcerative colitis. The global prevalence of IBD is rising, with over one million patients affected in the US alone. Adherent-invasive E. coli (AIEC) is a pathobiont frequently found in IBD biopsies. AIEC adhere to and invade epithelial cells, and can survive inside phagocytes in vitro. However, how AIEC contribute to IBD in vivo remains unclear. Here, we established a larval zevbrafish (Danio rerio) model to study the interplay between pre-existing intestinal inflammation and AIEC colonization of the gut. We used the pro-inflammatory drug dextran sulfate sodium (DSS) to induce colitis. This was followed by food-borne infection of larvae with AIEC using the protozoan Paramecium caudatum, a natural prey, as a vehicle. We show that AIEC more robustly colonizes the zebrafish gut, and persists for longer, compared to non-pathogenic E. coli. In addition, DSS induced colitis increases both bacterial burden and persistence in the larval gut. We benchmark our model against existing rodent models using two mutants deficient in the known AIEC virulence factors FimH and IbeA, which have virulence defects in both rodent and the larval zebrafish model. Finally, we show that AIEC colonization exacerbates DSS induced colitis and prevents recovery from inflammation. In conclusion, we established a high-throughput, genetically tractable model to study AIEC-host interactions in the context of chronic inflammation. IMPORTANCEAlthough inflammatory bowel diseases are on the rise, a lot remains to be learned about the link between IBD severity and the underlying cause. Although host genetics, microbiome, and environmental factors have all been shown to correlate with the development of IBD, cause and effect are difficult to disentangle in this context. For example, AIEC is a known pathobiont found in IBD patients, but it remains unclear if gut inflammation during IBD facilitates colonization with AIEC, or if AIEC colonization makes the host more susceptible towards pro-inflammatory stimuli. To develop successful therapeutics, it is critical to understand the mechanisms that contribute to AIEC infections in a susceptible host. Here, we show that the larval zebrafish model recapitulates key features of AIEC infections in other animal models, and can be utilized to address these gaps in knowledge.

microbiology↗

bioRxiv2020

Frequency-independent biological signal identification (FIBSI): A free program that simplifies intensive analysis of non-stationary time series data

Extracting biological signals from non-linear, dynamic and stochastic experimental data can be challenging, especially when the signal is non-stationary. Many currently available methods make assumptions about the data structure (e.g., signal is periodic, sufficient recording time) and modify the raw data in pre-processing using filters and/or transformations. With an agnostic approach to biological data analysis as a goal, we implemented a signal detection algorithm in Python that quantifies the dimensional properties of waveform deviations from baseline via a running fit function. We call the resulting free program frequency-independent biological signal identification (FIBSI). We demonstrate the utility of FIBSI on two disparate types of experimental data: in vitro whole-cell current-clamp electrophysiological recordings of rodent sensory neurons (i.e., nociceptors) and in vivo fluorescence image time-lapse movies capturing gastrointestinal motility in larval zebrafish. In rodent nociceptors, depolarizing fluctuations in membrane potential are irregular in shape and difficult to distinguish from noise. Using FIBSI, we determined that nociceptors from naïve mice generate larger, more frequent fluctuations compared to naïve rats, suggesting species-specific specializations in rodent nociceptors. In zebrafish, measuring gut motility is a useful tool for addressing developmental and disease-related mechanisms associated with gut function. However, available methods are laborious, technically complex, and/or not cost-effective. We developed and tested a novel assay that can characterize intestinal peristalsis using imaging time series datasets. We used FIBSI to identify muscle contractions in the fluorescence signals and compared their frequencies in unfed and fed larvae. Additionally, FIBSI allowed us to discriminate between peristalsis and oscillatory sphincter-like movements in functionally distinct gut segments (foregut, midgut, and cloaca). We conclude that FIBSI, which is freely available via GitHub, is widely useful for the unbiased analysis of non-stationary signals and extraction of biologically meaningful information from experimental time series data and can be employed for both descriptive and hypothesis-driven investigations.Author Summary Biologists increasingly work with large, complex experimental datasets. Those datasets often encode biologically meaningful signals along with background noise that is recorded along with the biological data during experiments. Background noise masks the real signal but originates from other sources, for example from the equipment used to perform the measurements or environmental disturbances. When it comes to analyzing the data, distinguishing between the real biological signals and the background noise can be very challenging. Many existing programs designed to help scientists with this problem are either difficult to use, not freely available, or only appropriate to use on very specific types of datasets. The research presented here embodies our goal of helping others to analyze their data by employing a powerful but novice-friendly program that describes multiple features of biological activity in its raw form without abstract transformations. We show the program’s applicability using two different kinds of biological activity measured in our labs. It is our hope that this will help others to analyze complex datasets more easily, thoroughly, and rigorously.Competing Interest StatementThe authors have declared no competing interest.View Full Text

physiology↗

bioRxiv2018

Bacterial outer membrane vesicles provide an alternative pathway for trafficking of type III secreted effectors into epithelial cells

Outer membrane vesicles (OMVs) are proteo-liposomes universally shed by Gram-negative bacteria. Their secretion is significantly enhanced by the transition into the intra-host milieu and OMVs have been shown to play critical roles during pathogenesis. Enterohemorrhagic Escherichia coli O157 (EHEC), causes diarrheal disease in humans, and soluble toxins including Shiga-like toxins that contribute to disease severity and clinical complications including hemolytic uremic syndrome, have been shown to be OMV associated. In addition to Shiga-like toxins, EHEC produces a type III secretion system (T3SS), and T3SS effectors are associated with colonization and disease severity in vivo. Here, we show that type III secreted substrates including translocators and effectors are incorporated into OMVs independent of type III secretion activity. EHEC strains with non-functional type III secretion systems shed more OMVs and vesicles enter host cells with accelerated kinetics compared to vesicles shed from wild type EHEC. The T3SS effector translocated intimin receptor (Tir) is trafficked from OMVs into host cells and localizes to the membrane. However, its clustering on the host membrane and co-localization with bacterial pedestals is intimin-dependent. We further show that OMV-delivered Tir can cross-complement an effector-deficient EHEC strain, demonstrating that OMV-associated effectors reach the host cell in a biologically intact form. Finally, we observe that the non-LEE encoded E3 ubiquitin ligase effector NleL is also trafficked to host cells via OMVs, where it ubiquitinylates its target kinase JNK. Together, these data demonstrate that trafficking of OMV-associated effectors is a novel and T3SS-independent pathway for the delivery of active effectors to host cells.

microbiology↗

bioRxiv2016

Lipopolysaccharide composition determines the preferred route and entry kinetics of bacterial outer membrane vesicles into host cells

Outer membrane vesicles are microvesicles shed by Gram-negative bacteria and play important roles in immune priming and disease pathogenesis. However, our current mechanistic understanding of vesicle - host cell interactions is limited by a lack of methods to study the kinetics of vesicle entry and cargo delivery to host cells in real-time. Here, we describe a highly sensitive method to study the kinetics of vesicle entry into host cells in real-time using a genetically encoded probe targeted to vesicles. We found that route of vesicular uptake, and thus entry kinetics and efficiency of cargo release, are determined by the chemical composition of the bacterial lipopolysaccharide. The presence of O-antigen facilitates receptor-independent entry, which enhances both rate and efficiency of cargo uptake by host cells. Collectively, our findings highlight the chemical composition of the bacterial cell wall as a major determinant of secretion-independent delivery of virulence factors during Gram-negative infections.

microbiology↗