Real time and online dynamic speckle assessment of growing bacteria using the method of motion history image

All-optical dual module platform for motility-based functional scrutiny of microencapsulated probiotic bacteria

Probiotic bacteria are widely used in pharmaceutics to offer health benefits. Microencapsulation is used to deliver probiotics into the human body. Capsules in the stomach have to keep bacteria constrained until release occurs in the intestine. Once outside, bacteria must maintain enough motility to reach the intestine walls. Here, we develop a platform based on two label-free optical modules for rapidly screening and ranking probiotic candidates in the laboratory. Bio-speckle dynamics assay tests the microencapsulation effectiveness by simulating the gastrointestinal transit. Then, a digital holographic microscope 3D-tracks their motility profiles at a single element level to rank the strains.

Evaluation of pitting corrosion by dynamic speckle pattern analysis

There is an increasing interest in non-destructive and real-time high-resolution approaches for corrosion studies in metals. In this paper, we propose the dynamic speckle pattern method as a low-cost, easy-to-implement, and quasi in-situ optical technique for the quantitative evaluation of pitting corrosion. This type of corrosion occurs in a specific area of a metallic structure and causes holes formation leading to structural failure. A Custom 450 stainless steel sample, placed in 3.5 wt% NaCl solution and applied to a [Formula: see text] potential to initiate the corrosion, is used as the sample. The speckle patterns formed by the scattering of a He-Ne laser light is changed over time due to any corrosion in the sample. The analysis of the time-integrate speckle pattern suggests that the growth rate of pitting decreases with time.

Detection of intralayer alignment in multicomponent lipids by dynamic speckle pattern analysis

Multicomponent mixtures of bilayer lipids, thanks to the coexistence of liquid-crystalline phases in their structures, may be used in the development of functional membranes. In such membranes interlayer ordering distributes across membrane lamellae, resulting in long-range alignment of phase-separated domains. In this paper, we explore the dynamics of this phenomenon by laser speckle pattern analysis. We show that cholesterol content decreases the activity, and the rate of the domains size development is related to the change of physical roughness of the multicomponent lipid mixture. Our results are in agreement with the previous experimental reports. However, our experimental procedure is an easy-to-implement and effective methodology.

Rapid Bacterial Detection in Urine Using Laser Scattering and Deep Learning Analysis

Images of laser scattering patterns generated by bacteria in urine are promising resources for deep learning. However, floating bacteria in urine produce dynamic scattering patterns and require deep learning of spatial and temporal features. We hypothesized that bacteria with variable bacterial densities and different Gram staining reactions would generate different speckle images. After deep learning of speckle patterns generated by various densities of bacteria in artificial urine, we validated the model in an independent set of clinical urine samples in a tertiary hospital. Even at a low bacterial density cutoff (1,000 CFU/mL), the model achieved a predictive accuracy of 90.9% for positive urine culture. At a cutoff of 50,000 CFU/mL, it showed a better accuracy of 98.5%. The model achieved satisfactory accuracy at both cutoff levels for predicting the Gram staining reaction. Considering only 30 min of analysis, our method appears as a new screening tool for predicting the presence of bacteria before urine culture. IMPORTANCE This study performed deep learning of multiple laser scattering patterns by the bacteria in urine to predict positive urine culture. Conventional urine analyzers have limited performance in identifying bacteria in urine. This novel method showed a satisfactory accuracy taking only 30 min of analysis without conventional urine culture. It was also developed to predict the Gram staining reaction of the bacteria. It can be used as a standalone screening tool for urinary tract infection.

Biospeckle Analysis and Biofilm Electrostatic Tests, Two Useful Methods in Microbiology

The development of more sensitive methodologies, capable of quickly detecting and monitoring a microbial population present in a specific biological matrix, as well as performing to allow for the study of all its metabolic changes (e.g., during the formation of biofilm) to occur, is an essential requirement for both well-being and the food industry. Two techniques, in particular, have gained the attention of scientists: The first is “biospeckle”, an optical technique representing an innovative tool for applications in food quality, food safety, and nutraceuticals. With this technique, we can quickly evaluate and monitor the presence of bacteria (or their proliferation) in a solid or liquid biological matrix. In addition, the technique is helpful in quantifying and optimizing the correct storage time of the pro-biotics, if they are entrapped in matrices such as alginate and follow their survival rate in simulated gastro-intestinal conditions. A second technique with great chances is the “biofilm electrostatic test” (BET). BET undoubtedly represents a fast, simple, and highly reproducible tool suitable for admitting the evaluation of the in vitro bacterial capacity in order to adhere through an electrostatic interaction with a pyro-electrified carrier after only 2 h of incubation. BET could represent the way for a quick and standardized evaluation of bacterial resistance among biofilm-producing microorganisms through a fast evaluation of the potential presence of the biofilm.

On the application of multi-parametric optical phenotyping of bacterial colonies for multipurpose microbiological diagnostics

The development of new diagnostics techniques and modalities is critical for early detection of microbial contamination. In this study, the novel integrated system for multi-parametric optical phenotyping and characterization of bacterial colonies, is presented. The system combines Mach-Zehnder interferometer with a spectral imaging system for capturing multispectral diffraction patterns and multispectral two-dimensional transmission maps of bacterial colonies, along with the simultaneous interferometric profilometry. The herein presented investigation was carried out on five representative bacteria species and nearly 3000 registered multispectral optical signatures. The interferograms were analyzed by four-step phase shift algorithm to reconstruct the colony profile to enable the obtaining of the comparable optical signatures. The dedicated image processing algorithms were used for extraction of quantitative features of these signatures. The random forest algorithm was applied for selection of the most predictive set of features, which were used in classification model based on Support-Vector Machine. Obtained results have shown that the use of multiple multispectral optical signatures provide a multi-parametric bacteria identification at an exceptionally high accuracy (99.4-100%), significantly better than in case of classification based on each of these signatures (multispectral diffraction patterns, two-dimensional transmission coefficient maps), separately. Obtained results revealed that analysis of multispectral signatures can also be applied for characterisation of physical, physicochemical and chemical properties of the bacterial colonies in the presence of the antimicrobial factors. Therefore, the proposed label-free, non-destructive optical technique has perspectives to be exploited in the multipurpose diagnostics and it can be used as a pre-screening tool in microbiological laboratories.

New live screening of plant-nematode interactions in the rhizosphere

Free living nematodes (FLN) are microscopic worms found in all soils. While many FLN species are beneficial to crops, some species cause significant damage by feeding on roots and vectoring viruses. With the planned legislative removal of traditionally used chemical treatments, identification of new ways to manage FLN populations has become a high priority. For this, more powerful screening systems are required to rapidly assess threats to crops and identify treatments efficiently. Here, we have developed new live assays for testing nematode responses to treatment by combining transparent soil microcosms, a new light sheet imaging technique termed Biospeckle Selective Plane Illumination Microscopy (BSPIM) for fast nematode detection, and Confocal Laser Scanning Microscopy for high resolution imaging. We show that BSPIM increased signal to noise ratios by up to 60 fold and allowed the automatic detection of FLN in transparent soil samples of 1.5 mL. Growing plant root systems were rapidly scanned for nematode abundance and activity, and FLN feeding behaviour and responses to chemical compounds observed in soil-like conditions. This approach could be used for direct monitoring of FLN activity either to develop new compounds that target economically damaging herbivorous nematodes or ensuring that beneficial species are not negatively impacted.

Dynamic laser speckle analyzed considering inhomogeneities in the biological sample

Dynamic laser speckle phenomenon allows a contactless and nondestructive way to monitor biological changes that are quantified by second-order statistics applied in the images in time using a secondary matrix known as time history of the speckle pattern (THSP). To avoid being time consuming, the traditional way to build the THSP restricts the data to a line or column. Our hypothesis is that the spatial restriction of the information could compromise the results, particularly when undesirable and unexpected optical inhomogeneities occur, such as in cell culture media. It tested a spatial random approach to collect the points to form a THSP. Cells in a culture medium and in drying paint, representing homogeneous samples in different levels, were tested, and a comparison with the traditional method was carried out. An alternative random selection based on a Gaussian distribution around a desired position was also presented. The results showed that the traditional protocol presented higher variation than the outcomes using the random method. The higher the inhomogeneity of the activity map, the higher the efficiency of the proposed method using random points. The Gaussian distribution proved to be useful when there was a well-defined area to monitor.