Culture-Free Detection of Crop Pathogens at the Single-Cell Level by Micro-Raman Spectroscopy

Label-free Raman microspectroscopic imaging with chemometrics for cellular investigation of apple ring rot and nondestructive early recognition using near-infrared reflection spectroscopy with machine learning

Apple ring rot caused by Botryosphaeria dothidea can cause fruit decay during the growth and storage stages of apple fruit. Understanding the infection process and cellular defense response at the cellular micro-level holds immense importance in the field of prevention and control. Consequently, there is a pressing need to develop suitable chemical imaging analysis methods. Here we proposed a label-free, high-throughput imaging method for cellular investigation of apple fruit ring rot infected by Botryosphaeria dothidea, based on confocal Raman microspectroscopic imaging technology combined with multivariate curve resolution-alternating least squares algorithm (MCR-ALS). We conducted Raman measurements on every apple fruit and obtain an image cube. This cube was then unfolded into an augmented matrix in a column-wise manner. We proceeded with simultaneous MCR-ALS analysis, resolving the single-substance spectrum and concentration profile from the mixed signals. Lastly, the accurate and pure molecular imaging of low methoxyl pectin, high methoxyl pectin, cellulose, lignin, and phenols were realized by refolding the resolved concentration data to construct the composition image. Thereafter, we realized the study of the spatial-temporal changes distribution of the above substances in the cuticle and cell wall of green and red apples at different stages of infection. The imaging method proposed in this paper is expected to provide a chemical imaging strategy for studying pathogen infection process and fruit defense response at the cellular level. In addition, by utilizing a fiber-optic probe near-infrared reflection spectrometer in conjunction with machine learning, we developed a rapid and non-destructive classification method. This method allows for the timely identification of apples exhibiting early infection by Botryosphaeria dothidea. Notably, both principal component analysis-quadratic discriminant analysis and support vector machine achieved a classification accuracy of 100%.

Control Phytophagous Nematodes By Engineering Phytosterol Dealkylation Caenorhabditis elegans as a Model

Plant-parasitic nematodes ingest and convert host phytosterols via dealkylation to cholesterol for both structural and hormonal requirements. The insect 24-dehydrocholesterol reductase (DHCR24) was shown in vitro as a committed enzyme in the dealkylation via chemical blocking. However, an increased brood size and ovulation rate, instead compromised development, were observed in the engineered nematode Caenorhabditis elegans where the DHCR24 gene was knocked down, indicating the relationship between DHCR24 and dealkylation and their function in nematodes remains illusive. In this study, a defect in C. elegans DHCR24 causes impaired growth of the nematode with sitosterol (a major component of phytosterols) as a sole sterol source. Plant sterols with rationally designed structure (null substrates for dealkylation) can't be converted to cholesterol in wild-type worms, and their development was completely halted. This study underpins the essential function of DHCR24 in nematodes and would be beneficial for the development of novel nematocidal strategies.

Engineering a marine microalga Chlorella sp. as the cell factory

The use of marine microalgae in industrial systems is attractive for converting CO2 into value-added products using saline water and sunlight. The plant nature and demonstrated industrial potential facilitate Chlorella spp. as excellent model organisms for both basic research and commercial application. However, the transformation method has not been developed in marine Chlorella spp., thus genetic engineering is hindered in exploiting the industrial potentialities of these strains. In this study, we provided a transformation protocol for the marine Chlorella strain MEM25, which showed robust characteristics, including high production of proteins and polyunsaturated fatty acids in multiple cultivation systems over various spatial-temporal scales. We showed that transformants could be obtained in a dramatically time-saving manner (comparable to Saccharomyces cerevisiae) with four functional proteins expressed properly. The transgenes are integrated into the genome and can be successfully inherited for more than two years. The development of a marine Chlorella transformation method, in combination with the complete genome, will greatly facilitate more comprehensive mechanism studies and provide possibilities to use this species as chassis for synthetic biology to produce value-added compounds with mutual advantage in neutralization of CO2 in commercial scales.

Characterization of conidial autofluorescence in powdery mildew

Autofluorescence is produced by endogenous fluorophores, such as NAD(P)H, lipofuscin, melanin, and riboflavin, indicating the accumulation of substances and the state of energy metabolism in organisms. As an obligate parasite, powdery mildew is wildly spread by air and parasitic crops. However, most identification studies have been based on morphology and molecular biology which were far too time- and labor-consuming, thus lacking characteristic, simple, and effective means. Using microscopy under the blue and cyan channels, we elaborated visible conidial autofluorescence in three powdery mildew species, Erysiphe quercicola, E. cichoracearum, and Podosphaera hibiscicola, with a sharp increase during the conidia senescence in E. quercicola. Additionally, the main spectral excitation detected by fluorescence spectrometery was 375 nm for these species, with a common emission peak at approximately 458-463 nm, and an additional trend at 487 nm for P. hibiscicola. Because NAD(P)H has a similar spectral feature, we further investigated the relation between NAD(P)H and conidial autofluorescence by fluorescence spectra. We observed that the reduced coenzymes prominently contributed to conidial autofluorescence; however, the conidial autofluorescence in P. hibiscicola displayed a different trend that may be affected by the oxidized coenzyme -NAD. Finally, the normalized average spectra of these three powdery mildew species and standard samples showed that the spectral trend of each species was similar but that the features in detail were specific and distinct based on principal component analysis. In conclusion, we showed and characterized conidial autofluorescence in three powdery mildew species for the first time. The specific conidial autofluorescence in these species provides a new idea for the development of field spore capture and identification devices for the discrimination of powdery mildew at the species level.

Raman Method in Identification of Species and Varieties, Assessment of Plant Maturity and Crop Quality—A Review

The present review covers reports discussing potential applications of the specificity of Raman techniques in the advancement of digital farming, in line with an assumption of yield maximisation with minimum environmental impact of agriculture. Raman is an optical spectroscopy method which can be used to perform immediate, label-free detection and quantification of key compounds without destroying the sample. The authors particularly focused on the reports discussing the use of Raman spectroscopy in monitoring the physiological status of plants, assessing crop maturity and quality, plant pathology and ripening, and identifying plant species and their varieties. In recent years, research reports have presented evidence confirming the effectiveness of Raman spectroscopy in identifying biotic and abiotic stresses in plants as well as in phenotyping and digital selection of plants in farming. Raman techniques used in precision agriculture can significantly improve capacities for farming management, crop quality assessment, as well as biological and chemical contaminant detection, thereby contributing to food safety as well as the productivity and profitability of agriculture. This review aims to increase the awareness of the growing potential of Raman spectroscopy in agriculture among plant breeders, geneticists, farmers and engineers.

Opening up the Single-Cell Toolbox for Microbial Natural Products Research

The diverse microbes that produce natural products represent an important source of novel therapeutics, drug leads, and scientific tools. However, the vast majority have not been grown in axenic culture and are members of complex communities. While meta-'omic methods such as metagenomics, -transcriptomics, and -proteomics reveal collective molecular features of this "microbial dark matter", the study of individual microbiome members can be challenging. To address these limits, a number of techniques with single-bacterial resolution have been developed in the last decade and a half. While several of these are embraced by microbial ecologists, there has been less use by researchers interested in mining microbes for natural products. In this review, we discuss the available and emerging techniques for targeted single-cell analysis with a particular focus on applications to the discovery and study of natural products.

Raman-Based Diagnostics of Biotic and Abiotic Stresses in Plants. A Review

Digital farming is a novel agricultural philosophy that aims to maximize a crop yield with the minimal environmental impact. Digital farming requires the development of technologies that can work directly in the field providing information about a plant health. Raman spectroscopy (RS) is an emerging analytical technique that can be used for non-invasive, non-destructive, and confirmatory diagnostics of diseases, as well as the nutrient deficiencies in plants. RS is also capable of probing nutritional content of grains, as well as highly accurate identification plant species and their varieties. This allows for Raman-based phenotyping and digital selection of plants. These pieces of evidence suggest that RS can be used for chemical-free surveillance of plant health directly in the field. High selectivity and specificity of this technique show that RS may transform the agriculture in the US. This review critically discusses the most recent research articles that demonstrate the use of RS in diagnostics of abiotic and abiotic stresses in plants, as well as the identification of plant species and their nutritional analysis.

Transparent soil microcosms for live-cell imaging and non-destructive stable isotope probing of soil microorganisms

Microscale processes are critically important to soil ecology and biogeochemistry yet are difficult to study due to soil's opacity and complexity. To advance the study of soil processes, we constructed transparent soil microcosms that enable the visualization of microbes via fluorescence microscopy and the non-destructive measurement of microbial activity and carbon uptake in situ via Raman microspectroscopy. We assessed the polymer Nafion and the crystal cryolite as optically transparent soil substrates. We demonstrated that both substrates enable the growth, maintenance, and visualization of microbial cells in three dimensions over time, and are compatible with stable isotope probing using Raman. We applied this system to ascertain that after a dry-down/rewetting cycle, bacteria on and near dead fungal hyphae were more metabolically active than those far from hyphae. These data underscore the impact fungi have facilitating bacterial survival in fluctuating conditions and how these microcosms can yield insights into microscale microbial activities.

A Quantitative Bacteria Monitoring and Killing Platform Based on Electron Transfer from Bacteria to a Semiconductor

A platform with both bacteria killing and sensing capabilities is crucial for monitoring the entire bacteria-related process on biomaterials and biomedical devices. Electron transfer (ET) between the bacteria and a Au-loaded semiconductor (ZnO) is observed to be the primary factor for effective bacteria sensing and fast bacteria killing. The electrons produce a saturation current that varies linearly with the bacteria number, semi-logarithmically, with R² of 0.98825, thus providing an excellent tool to count bacteria quantitatively in real-time. Furthermore, ET leads to continuous electron loss killing of about 80% of Escherichia coli in only 1 h without light. The modularity and extendability of this ET-based platform are also demonstrated by the excellent results obtained from other semiconductor/substrate systems and the stability is confirmed by recycling tests. The underlying mechanism for the dual functions is not due to conventional attributed Zn²⁺ leaching or photocatalysis but instead electrical interactions upon direct contact. The results reveal the capability of real-time detection of bacteria based on ET while providing information about the antibacterial behavior of ZnO-based materials especially in the early stage. The concept can be readily incorporated into the design of smart and miniaturized devices that can sense and kill bacteria simultaneously.

Rapid detection of the aspergillosis biomarker triacetylfusarinine C using interference-enhanced Raman spectroscopy

Triacetylfusarinine C (TAFC) is a siderophore produced by certain fungal species and might serve as a highly useful biomarker for the fast diagnosis of invasive aspergillosis. Due to its renal elimination, the biomarker is found in urine samples of patients suffering from Aspergillus infections. Accordingly, non-invasive diagnosis from this easily obtainable body fluid is possible. Within our contribution, we demonstrate how Raman microspectroscopy enables a sensitive and specific detection of TAFC. We characterized the TAFC iron complex and its iron-free form using conventional and interference-enhanced Raman spectroscopy (IERS) and compared the spectra with the related compound ferrioxamine B, which is produced by bacterial species. Even though IERS only offers a moderate enhancement of the Raman signal, the employment of respective substrates allowed lowering the detection limit to reach the clinically relevant range. The achieved limit of detection using IERS was 0.5 ng of TAFC, which is already well within the clinically relevant range. By using an extraction protocol, we were able to detect 1.4 μg/mL TAFC via IERS from urine within less than 3 h including sample preparation and data analysis. We could further show that TAFC and ferrioxamine B can be clearly distinguished by means of their Raman spectra even in very low concentrations.

Rapid screening and quantitative detection of Salmonella using a quantum dot nanobead-based biosensor

A quantum dot nanobead-based sensor is demonstrated for Salmonella detection with balanced sensitivity, specificity and high accuracy.

Applications of Raman spectroscopy in the development of cell therapies: state of the art and future perspectives

This comprehensive review article discusses current and future perspectives of Raman spectroscopy-based analyses of cell therapy processes and products.

Detection of Clavibacter michiganensis subsp. michiganensis Assisted by Micro-Raman Spectroscopy under Laboratory Conditions

Clavibacter michiganensis subsp. michiganesis (Cmm) is a quarantine-worthy pest in México. The implementation and validation of new technologies is necessary to reduce the time for bacterial detection in laboratory conditions and Raman spectroscopy is an ambitious technology that has all of the features needed to characterize and identify bacteria. Under controlled conditions a contagion process was induced with Cmm, the disease epidemiology was monitored. Micro-Raman spectroscopy (532 nm λ laser) technique was evaluated its performance at assisting on Cmm detection through its characteristic Raman spectrum fingerprint. Our experiment was conducted with tomato plants in a completely randomized block experimental design (13 plants × 4 rows). The Cmm infection was confirmed by 16S rDNA and plants showed symptoms from 48 to 72 h after inoculation, the evolution of the incidence and severity on plant population varied over time and it kept an aggregated spatial pattern. The contagion process reached 79% just 24 days after the epidemic was induced. Micro-Raman spectroscopy proved its speed, efficiency and usefulness as a non-destructive method for the preliminary detection of Cmm. Carotenoid specific bands with wavelengths at 1146 and 1510 cm-1 were the distinguishable markers. Chemometric analyses showed the best performance by the implementation of PCA-LDA supervised classification algorithms applied over Raman spectrum data with 100% of performance in metrics of classifiers (sensitivity, specificity, accuracy, negative and positive predictive value) that allowed us to differentiate Cmm from other endophytic bacteria (Bacillus and Pantoea). The unsupervised KMeans algorithm showed good performance (100, 96, 98, 91 y 100%, respectively).