Brian Luna

Clinical and Pathophysiological Overview of Acinetobacter Infections: a Century of Challenges

SUMMARY Acinetobacter is a complex genus, and historically, there has been confusion about the existence of multiple species. The species commonly cause nosocomial infections, predominantly aspiration pneumonia and catheter-associated bacteremia, but can also cause soft tissue and urinary tract infections. Community-acquired infections by Acinetobacter spp. are increasingly reported. Transmission of Acinetobacter and subsequent disease is facilitated by the organisms environmental tenacity, resistance to desiccation, and evasion of host immunity. The virulence properties demonstrated by Acinetobacter spp. primarily stem from evasion of rapid clearance by the innate immune system, effectively enabling high bacterial density that triggers lipopolysaccharide (LPS)–Toll-like receptor 4 (TLR4)-mediated sepsis. Capsular polysaccharide is a critical virulence factor that enables immune evasion, while LPS triggers septic shock. However, the primary driver of clinical outcome is antibiotic resistance. Administration of initially effective therapy is key to improving survival, reducing 30-day mortality threefold. Regrettably, due to the high frequency of this organism having an extreme drug resistance (XDR) phenotype, early initiation of effective therapy is a major clinical challenge. Given its high rate of antibiotic resistance and abysmal outcomes (up to 70% mortality rate from infections caused by XDR strains in some case series), new preventative and therapeutic options for Acinetobacter spp. are desperately needed.

Mycobacterium tuberculosis dysregulates MMP/TIMP balance to drive rapid cavitation and unrestrained bacterial proliferation.

Active tuberculosis (TB) often presents with advanced pulmonary disease, including irreversible lung damage and cavities. Cavitary pathology contributes to antibiotic failure, transmission, morbidity and mortality. Matrix metalloproteinases (MMPs), in particular MMP‐1, are implicated in TB pathogenesis. We explored the mechanisms relating MMP/TIMP imbalance to cavity formation in a modified rabbit model of cavitary TB. Our model resulted in consistent progression of consolidation to human‐like cavities (100% by day 28), with resultant bacillary burdens (>107 CFU/g) far greater than those found in matched granulomatous tissue (105 CFU/g). Using a novel, breath‐hold computed tomography (CT) scanning and image analysis protocol, we showed that cavities developed rapidly from areas of densely consolidated tissue. Radiological change correlated with a decrease in functional lung tissue, as estimated by changes in lung density during controlled pulmonary expansion (R2 = 0.6356, p < 0.0001). We demonstrated that the expression of interstitial collagenase (MMP‐1) was specifically greater in cavitary compared to granulomatous lesions (p < 0.01), and that TIMP‐3 significantly decreased at the cavity surface. Our findings demonstrated that an MMP‐1/TIMP imbalance is associated with the progression of consolidated regions to cavities containing very high bacterial burdens. Our model provided mechanistic insight, correlating with human disease at the pathological, microbiological and molecular levels. It also provided a strategy to investigate therapeutics in the context of complex TB pathology. We used these findings to predict a MMP/TIMP balance in active TB and confirmed this in human plasma, revealing the potential of MMP/TIMP levels as key components of a diagnostic matrix aimed at distinguishing active from latent TB (PPV = 92.9%, 95% CI 66.1–99.8%, NPV = 85.6%; 95% CI 77.0–91.9%). Copyright

Gene Expression of Mycobacterium tuberculosis Putative Transcription Factors whiB1-7 in Redox Environments

The seven WhiB proteins of Mycobacterium tuberculosis (M.tb) are widely believed to be redox-sensing transcription factors due to their binding of iron-sulfur clusters and similarities to DNA binding proteins. Here, we explored the nature of this hypothesized relationship. We exposed M.tb to physiologic conditions such as gradual hypoxia, nitric oxide (NO), cyclic AMP and in vivo conditions, and measured transcription of the whiB genes. We found whiB3 to be induced both by hypoxia and NO, whiB7 to be induced in macrophage-like cells, and whiB4 to be induced in mouse lung. Cyclic AMP induced whiB1,−2, −4, −6 and −7. Our data indicate that the M.tb whiB genes are induced independently by various stimuli which may add versatility to their suggested redox-sensing properties.

Segmentation of PET Images for Computer-Aided Functional Quantification of Tuberculosis in Small Animal Models

Pulmonary infections often cause spatially diffuse and multi-focal radiotracer uptake in positron emission tomography (PET) images, which makes accurate quantification of the disease extent challenging. Image segmentation plays a vital role in quantifying uptake due to the distributed nature of immuno-pathology and associated metabolic activities in pulmonary infection, specifically tuberculosis (TB). For this task, thresholding-based segmentation methods may be better suited over other methods; however, performance of the thresholding-based methods depend on the selection of thresholding parameters, which are often suboptimal. Several optimal thresholding techniques have been proposed in the literature, but there is currently no consensus on how to determine the optimal threshold for precise identification of spatially diffuse and multi-focal radiotracer uptake. In this study, we propose a method to select optimal thresholding levels by utilizing a novel intensity affinity metric within the affinity propagation clustering framework. We tested the proposed method against 70 longitudinal PET images of rabbits infected with TB. The overall dice similarity coefficient between the segmentation from the proposed method and two expert segmentations was found to be 91.25 ±8.01% with a sensitivity of 88.80 ±12.59% and a specificity of 96.01 ±9.20%. High accuracy and heightened efficiency of our proposed method, as compared to other PET image segmentation methods, were reported with various quantification metrics.

A computational pipeline for quantification of pulmonary infections in small animal models using serial PET-CT imaging

BackgroundInfectious diseases are the second leading cause of death worldwide. In order to better understand and treat them, an accurate evaluation using multi-modal imaging techniques for anatomical and functional characterizations is needed. For non-invasive imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), there have been many engineering improvements that have significantly enhanced the resolution and contrast of the images, but there are still insufficient computational algorithms available for researchers to use when accurately quantifying imaging data from anatomical structures and functional biological processes. Since the development of such tools may potentially translate basic research into the clinic, this study focuses on the development of a quantitative and qualitative image analysis platform that provides a computational radiology perspective for pulmonary infections in small animal models. Specifically, we designed (a) a fast and robust automated and semi-automated image analysis platform and a quantification tool that can facilitate accurate diagnostic measurements of pulmonary lesions as well as volumetric measurements of anatomical structures, and incorporated (b) an image registration pipeline to our proposed framework for volumetric comparison of serial scans. This is an important investigational tool for small animal infectious disease models that can help advance researchers’ understanding of infectious diseases.MethodsWe tested the utility of our proposed methodology by using sequentially acquired CT and PET images of rabbit, ferret, and mouse models with respiratory infections of Mycobacterium tuberculosis (TB), H1N1 flu virus, and an aerosolized respiratory pathogen (necrotic TB) for a total of 92, 44, and 24 scans for the respective studies with half of the scans from CT and the other half from PET. Institutional Administrative Panel on Laboratory Animal Care approvals were obtained prior to conducting this research. First, the proposed computational framework registered PET and CT images to provide spatial correspondences between images. Second, the lungs from the CT scans were segmented using an interactive region growing (IRG) segmentation algorithm with mathematical morphology operations to avoid false positive (FP) uptake in PET images. Finally, we segmented significant radiotracer uptake from the PET images in lung regions determined from CT and computed metabolic volumes of the significant uptake. All segmentation processes were compared with expert radiologists’ delineations (ground truths). Metabolic and gross volume of lesions were automatically computed with the segmentation processes using PET and CT images, and percentage changes in those volumes over time were calculated. (Continued on next page)(Continued from previous page) Standardized uptake value (SUV) analysis from PET images was conducted as a complementary quantitative metric for disease severity assessment. Thus, severity and extent of pulmonary lesions were examined through both PET and CT images using the aforementioned quantification metrics outputted from the proposed framework.ResultsEach animal study was evaluated within the same subject class, and all steps of the proposed methodology were evaluated separately. We quantified the accuracy of the proposed algorithm with respect to the state-of-the-art segmentation algorithms. For evaluation of the segmentation results, dice similarity coefficient (DSC) as an overlap measure and Haussdorf distance as a shape dissimilarity measure were used. Significant correlations regarding the estimated lesion volumes were obtained both in CT and PET images with respect to the ground truths (R2=0.8922,p<0.01 and R2=0.8664,p<0.01, respectively). The segmentation accuracy (DSC (%)) was 93.4±4.5% for normal lung CT scans and 86.0±7.1% for pathological lung CT scans. Experiments showed excellent agreements (all above 85%) with expert evaluations for both structural and functional imaging modalities. Apart from quantitative analysis of each animal, we also qualitatively showed how metabolic volumes were changing over time by examining serial PET/CT scans. Evaluation of the registration processes was based on precisely defined anatomical landmark points by expert clinicians. An average of 2.66, 3.93, and 2.52 mm errors was found in rabbit, ferret, and mouse data (all within the resolution limits), respectively. Quantitative results obtained from the proposed methodology were visually related to the progress and severity of the pulmonary infections as verified by the participating radiologists. Moreover, we demonstrated that lesions due to the infections were metabolically active and appeared multi-focal in nature, and we observed similar patterns in the CT images as well. Consolidation and ground glass opacity were the main abnormal imaging patterns and consistently appeared in all CT images. We also found that the gross and metabolic lesion volume percentage follow the same trend as the SUV-based evaluation in the longitudinal analysis.ConclusionsWe explored the feasibility of using PET and CT imaging modalities in three distinct small animal models for two diverse pulmonary infections. We concluded from the clinical findings, derived from the proposed computational pipeline, that PET-CT imaging is an invaluable hybrid modality for tracking pulmonary infections longitudinally in small animals and has great potential to become routinely used in clinics. Our proposed methodology showed that automated computed-aided lesion detection and quantification of pulmonary infections in small animal models are efficient and accurate as compared to the clinical standard of manual and semi-automated approaches. Automated analysis of images in pre-clinical applications can increase the efficiency and quality of pre-clinical findings that ultimately inform downstream experimental design in human clinical studies; this innovation will allow researchers and clinicians to more effectively allocate study resources with respect to research demands without compromising accuracy.

In Vivo Prediction of Tuberculosis-Associated Cavity Formation in Rabbits

The presence of cavitary lesions in patients with tuberculosis poses a significant clinical concern due to the risk of infectivity and the risk of antibiotic treatment failure. We describe 2 algorithms that use noninvasive positron emission tomography (PET) and computed tomography (CT) to predict the development of cavitary lesions in rabbits. Analysis of the PET region of interest predicted cavitary disease with 100% sensitivity and 76% specificity, and analysis of the CT region of interest predicted cavitary disease with 83.3% sensitivity and 76.9% specificity. Our results show that restricting our analysis to regions with high [(18)F]-fluorodeoxyglucose uptake provided the best combination of sensitivity and specificity.

Robust segmentation and accurate target definition for positron emission tomography images using Affinity Propagation

Distributed inflammation in infectious diseases cause variable uptake regions in positron emission tomography (PET) images. Due to this distributed nature of immuno-pathology and associated PET uptake, intensity based methods are much better suited over region based methods for segmentation. The most commonly used intensity based segmentation is thresholding, but it has a major drawback of a lack of consensus on the selection of the thresholding value. We propose a method to select an optimal thresholding value by utilizing a novel similarity metric between the data points along the gray-level histogram of the image then using Affinity Propagation (AP) to cluster the intensities based on this metric. This method is tested against the PET images of rabbits infected with tuberculosis with distributed uptakes with promising results.

Cathepsin K Contributes to Cavitation and Collagen Turnover in Pulmonary Tuberculosis

Cavitation in tuberculosis enables highly efficient person-to-person aerosol transmission. We performed transcriptomics in the rabbit cavitary tuberculosis model. Among 17 318 transcripts, we identified 22 upregulated proteases. Five type I collagenases were overrepresented: cathepsin K (CTSK), mast cell chymase-1 (CMA1), matrix metalloproteinase 1 (MMP-1), MMP-13, and MMP-14. Studies of collagen turnover markers, specifically, collagen type I C-terminal propeptide (CICP), urinary deoxypyridinoline (DPD), and urinary helical peptide, revealed that cavitation in tuberculosis leads to both type I collagen destruction and synthesis and that proteases other than MMP-1, MMP-13, and MMP-14 are involved, suggesting a key role for CTSK. We confirmed the importance of CTSK upregulation in human lung specimens, using immunohistochemical analysis, which revealed perigranulomatous staining for CTSK, and we showed that CTSK levels were increased in the serum of patients with tuberculosis, compared with those in controls (3.3 vs 0.3 ng/mL; P = .005).

Monoclonal Antibody Protects Against Acinetobacter baumannii Infection by Enhancing Bacterial Clearance and Evading Sepsis

Background Extremely drug-resistant (XDR) Acinetobacter baumannii is one of the most commonly encountered, highly resistant pathogens requiring novel therapeutic interventions. Methods We developed C8, a monoclonal antibody (mAb), by immunizing mice with sublethal inocula of a hypervirulent XDR clinical isolate. Results C8 targets capsular carbohydrate on the bacterial surface, enhancing opsonophagocytosis. Treating with a single dose of C8 as low as 0.5 μg/mouse (0.0167 mg/kg) markedly improved survival in lethal bacteremic sepsis and aspiration pneumonia models of XDR A. baumannii infection. C8 was also synergistic with colistin, substantially improving survival compared to monotherapy. Treatment with C8 significantly reduced blood bacterial density, cytokine production (tumor necrosis factor α, interleukin [IL] 6, IL-1β, and IL-10), and sepsis biomarkers. Serial in vitro passaging of A. baumannii in the presence of C8 did not cause loss of mAb binding to the bacteria, but did result in emergence of less-virulent mutants that were more susceptible to macrophage uptake. Finally, we developed a highly humanized variant of C8 that retains opsonophagocytic activity in murine and human macrophages and rescued mice from lethal infection. Conclusions We describe a promising and novel mAb as therapy for lethal, XDR A. baumannii infections, and demonstrate that it synergistically improves outcomes in combination with antibiotics.

Injection of dsRNA into female A. aegypti mosquitos.

Reverse genetic approaches have proven extremely useful for determining which genes underly resistance to vector pathogens in mosquitoes. This video protocol illustrates a method used by the James lab to inject dsRNA into female A. aegypti mosquitoes, which harbor the dengue virus. The technique for calibrating injection needles, manipulating the injection setup, and injecting dsRNA into the thorax is illustrated.