Development and validation of a quick, automated, and reproducible ATR FT-IR spectroscopy machine-learning model for Klebsiella pneumoniae typing.

The reliability of Fourier-transform infrared (FT-IR) spectroscopy for Klebsiella pneumoniae typing and outbreak control has been previously assessed, but issues remain in standardization and reproducibility. We developed and validated a reproducible FT-IR with attenuated total reflectance (ATR) workflow for the identification of K. pneumoniae lineages. We used 293 isolates representing multidrug-resistant K. pneumoniae lineages causing outbreaks worldwide (2002-2021) to train a random forest classification (RF) model based on capsular (KL)-type discrimination. This model was validated with 280 contemporaneous isolates (2021-2022), using wzi sequencing and whole-genome sequencing as references. Repeatability and reproducibility were tested in different culture media and instruments throughout time. Our RF model allowed the classification of 33 capsular (KL)-types and up to 36 clinically relevant K. pneumoniae lineages based on the discrimination of specific KL- and O-type combinations. We obtained high rates of accuracy (89%), sensitivity (88%), and specificity (92%), including from cultures obtained directly from the clinical sample, allowing to obtain typing information the same day bacteria are identified. The workflow was reproducible in different instruments throughout time (>98% correct predictions). Direct colony application, spectral acquisition, and automated KL prediction through Clover MS Data analysis software allow a short time-to-result (5 min/isolate). We demonstrated that FT-IR ATR spectroscopy provides meaningful, reproducible, and accurate information at a very early stage (as soon as bacterial identification) to support infection control and public health surveillance. The high robustness together with automated and flexible workflows for data analysis provide opportunities to consolidate real-time applications at a global level. IMPORTANCE We created and validated an automated and simple workflow for the identification of clinically relevant Klebsiella pneumoniae lineages by FT-IR spectroscopy and machine-learning, a method that can be extremely useful to provide quick and reliable typing information to support real-time decisions of outbreak management and infection control. This method and workflow is of interest to support clinical microbiology diagnostics and to aid public health surveillance.

Direct Detection of Carbapenemase-Producing Klebsiella pneumoniae by MALDI-TOF Analysis of Full Spectra Applying Machine Learning.

MALDI-TOF MS is considered to be an important tool for the future development of rapid microbiological techniques. We propose the application of MALDI-TOF MS as a dual technique for the identification of bacteria and the detection of resistance, with no extra hands-on procedures. We have developed a machine learning approach that uses the random forest algorithm for the direct prediction of carbapenemase-producing Klebsiella pneumoniae (CPK) isolates, based on the spectra of complete cells. For this purpose, we used a database of 4,547 mass spectra profiles, including 715 unduplicated clinical isolates that are represented by 324 CPK with 37 different ST. The impact of the culture medium was determinant in the CPK prediction, being that the isolates were tested and cultured in the same media, compared to the isolates used to build the model (blood agar). The proposed method has an accuracy of 97.83% for the prediction of CPK and an accuracy of 95.24% for the prediction of OXA-48 or KPC carriage. For the CPK prediction, the RF algorithm yielded a value of 1.00 for both the area under the receiver operating characteristic curve and the area under the precision-recall curve. The contribution of individual mass peaks to the CPK prediction was determined using Shapley values, which revealed that the complete proteome, rather than a series of mass peaks or potential biomarkers (as previously suggested), is responsible for the algorithm-based classification. Thus, the use of the full spectrum, as proposed here, with a pattern-matching analytical algorithm produced the best outcome. The use of MALDI-TOF MS coupled with machine learning algorithm processing enabled the identification of CPK isolates within only a few minutes, thereby reducing the time to detection of resistance.

Automatic Discrimination of Species within the Enterobacter cloacae Complex Using Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry and Supervised Algorithms.

The Enterobacter cloacae complex (ECC) encompasses heterogeneous clusters of species that have been associated with nosocomial outbreaks. These species may have different acquired antimicrobial resistance and virulence mechanisms, and their identification is challenging. This study aims to develop predictive models based on matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) profiles and machine learning for species-level identification. A total of 219 ECC and 118 Klebsiella aerogenes clinical isolates from three hospitals were included. The capability of the proposed method to differentiate the most common ECC species (Enterobacter asburiae, Enterobacter kobei, Enterobacter hormaechei, Enterobacter roggenkampii, Enterobacter ludwigii, and Enterobacter bugandensis) and K. aerogenes was demonstrated by applying unsupervised hierarchical clustering with principal-component analysis (PCA) preprocessing. We observed a distinctive clustering of E. hormaechei and K. aerogenes and a clear trend for the rest of the ECC species to be differentiated over the development data set. Thus, we developed supervised, nonlinear predictive models (support vector machine with radial basis function and random forest). The external validation of these models with protein spectra from two participating hospitals yielded 100% correct species-level assignment for E. asburiae, E. kobei, and E. roggenkampii and between 91.2% and 98.0% for the remaining ECC species; with data analyzed in the three participating centers, the accuracy was close to 100%. Similar results were obtained with the Mass Spectrometric Identification (MSI) database developed recently (https://msi.happy-dev.fr) except in the case of E. hormaechei, which was more accurately identified with the random forest algorithm. In short, MALDI-TOF MS combined with machine learning was demonstrated to be a rapid and accurate method for the differentiation of ECC species.

A global synthesis of high-resolution stable isotope data from benthic foraminifera of the last deglaciation.

We present the first version of the Ocean Circulation and Carbon Cycling (OC3) working group database, of oxygen and carbon stable isotope ratios from benthic foraminifera in deep ocean sediment cores from the Last Glacial Maximum (LGM, 23-19 ky) to the Holocene (<10 ky) with a particular focus on the early last deglaciation (19-15 ky BP). It includes 287 globally distributed coring sites, with metadata, isotopic and chronostratigraphic information, and age models. A quality check was performed for all data and age models, and sites with at least millennial resolution were preferred. Deep water mass structure as well as differences between the early deglaciation and LGM are captured by the data, even though its coverage is still sparse in many regions. We find high correlations among time series calculated with different age models at sites that allow such analysis. The database provides a useful dynamical approach to map physical and biogeochemical changes of the ocean throughout the last deglaciation.

Identification of Mycobacterium abscessus Subspecies by MALDI-TOF Mass Spectrometry and Machine Learning.

Mycobacterium abscessus is one of the most common and pathogenic nontuberculous mycobacteria (NTM) isolated in clinical laboratories. It consists of three subspecies: M. abscessus subsp. abscessus, M. abscessus subsp. bolletii, and M. abscessus subsp. massiliense. Due to their different antibiotic susceptibility pattern, a rapid and accurate identification method is necessary for their differentiation. Although matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) has proven useful for NTM identification, the differentiation of M. abscessus subspecies is challenging. In this study, a collection of 325 clinical isolates of M. abscessus was used for MALDI-TOF MS analysis and for the development of machine learning predictive models based on MALDI-TOF MS protein spectra. Overall, using a random forest model with several confidence criteria (samples by triplicate and similarity values >60%), a total of 96.5% of isolates were correctly identified at the subspecies level. Moreover, an improved model with Spanish isolates was able to identify 88.9% of strains collected in other countries. In addition, differences in culture media, colony morphology, and geographic origin of the strains were evaluated, showing that the latter had an impact on the protein spectra. Finally, after studying all protein peaks previously reported for this species, two novel peaks with potential for subspecies differentiation were found. Therefore, machine learning methodology has proven to be a promising approach for rapid and accurate identification of subspecies of M. abscessus using MALDI-TOF MS.

Ultrasensitive and rapid identification of ESRI developer- and piperacillin/tazobactam-resistant Escherichia coli by the MALDIpiptaz test.

BACKGROUND: The excessive use of piperacillin/tazobactam (P/T) has promoted the emergence of P/T-resistant Enterobacterales. We reported that in Escherichia coli, P/T contributes to the development of extended-spectrum resistance to ß-lactam/ß-lactamase inhibitor (BL/BLI) (ESRI) in isolates that are P/T susceptible but have low-level resistance to BL/BLI. Currently, the detection of P/T resistance relying on conventional methods is time-consuming. To overcome this issue, we developed a cost-effective test based on MALDI-MS technology, called MALDIpiptaz, which aims to detect P/T resistance and ESRI developers in E. coli. METHODS: We used automated Clover MS Data Analysis software to analyse the protein profile spectra obtained by MALDI-MS from a collection of 248 E. coli isolates (91 P/T-resistant, 81 ESRI developers and 76 P/T-susceptible). This software allowed to preprocess all the spectra to build different peak matrices that were analysed by machine learning algorithms. RESULTS: We demonstrated that MALDIpiptaz can efficiently and rapidly (15 min) discriminate between P/T-resistant, ESRI developer and P/T-susceptible isolates and allowed the correct classification between ESRI developers from their isogenic resistance to P/T. CONCLUSION: The combination of excellent performance and cost-effectiveness are all desirable attributes, allowing the MALDIpiptaz test to be a useful tool for the rapid determination of P/T resistance in clinically relevant E. coli isolates.

Rapid and Reproducible MALDI-TOF-Based Method for the Detection of Vancomycin-Resistant Enterococcus faecium Using Classifying Algorithms.

Vancomycin-resistant Enterococcus faecium represents a health threat due to its ability to spread and cause outbreaks. MALDI-TOF MS has demonstrated its usefulness for E. faecium identification, but its implementation for antimicrobial resistance detection is still under evaluation. This study assesses the repeatability of MALDI-TOF MS for peak analysis and its performance in the discrimination of vancomycin-susceptible (VSE) from vancomycin-resistant isolates (VRE). The study was carried out on protein spectra from 178 E. faecium unique clinical isolates-92 VSE, 31 VanA VRE, 55 VanB VRE-, processed with Clover MS Data Analysis software. Technical and biological repeatability were assayed. Unsupervised (principal component analysis, (PCA)) and supervised algorithms (support vector machine (SVM), random forest (RF) and partial least squares-discriminant analysis (PLS-DA)) were applied. The repeatability assay was performed with 18 peaks common to VSE and VRE with intensities above 1.0% of the maximum peak intensity. It showed lower variability for normalized data and for the peaks within the 3000-9000 m/z range. It was found that 80.9%, 79.2% and 77.5% VSE vs. VRE discrimination was achieved by applying SVM, RF and PLS-DA, respectively. Correct internal differentiation of VanA from VanB VRE isolates was obtained by SVM in 86.6% cases. The implementation of MALDI-TOF MS and peak analysis could represent a rapid and effective tool for VRE screening. However, further improvements are needed to increase the accuracy of this approach.

Detection of azole resistance in Aspergillus fumigatus complex isolates using MALDI-TOF mass spectrometry.

OBJECTIVES: The main goal of this study was to accurately detect azole resistance in species of the Aspergillus fumigatus complex by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). METHODS: Identification of isolates (n = 868) was done with MALDI-TOF MS using both commercial and in-house libraries. To determine azole susceptibility, the EUCAST E.Def. 9.3.2 method was applied as the reference standard. Identification of resistant isolates was confirmed by DNA sequence analysis. Protein spectra obtained by MALDI-TOF MS were analysed to differentiate species within the A. fumigatus complex and to detect azole-resistant A. fumigatus sensu stricto isolates. RESULTS: Correct discrimination of A. fumigatus sensu stricto from cryptic species was accomplished in 100% of the cases applying principal component analysis (PCA) to protein spectra generated by MALDI-TOF MS. Furthermore, a specific peak (4586 m/z) was found to be present only in cryptic species. The application of partial least squares (PLS) discriminant analysis allowed 98.43% (±0.038) discrimination between susceptible and azole-resistant A. fumigatus sensu stricto isolates. Finally, based on PLS and SVM, A. fumigatus sensu stricto isolates with different cyp51A gene mutations were correctly clustered in 91.5% of the cases. CONCLUSIONS: MALDI-TOF MS combined with peak analysis is a novel tool that allows the differentiation of A. fumigatus sensu stricto from other species within the A. fumigatus complex, as well as the detection of azole-resistant A. fumigatus sensu stricto. Although further studies are still needed, the results reported here show the great potential of MALDI-TOF and machine learning for the rapid detection of azole-resistant Aspergillus fumigatus isolates from clinical origins.

An Improved Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Data Analysis Pipeline for the Identification of Carbapenemase-Producing Klebsiella pneumoniae.

The increasing emergence of carbapenemase-producing Klebsiella pneumoniae (CPK) isolates is a global health alarm. Rapid methods that require minimum sample preparation and rapid data analysis are urgently required. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been used by clinical laboratories for identification of antibiotic-resistant bacteria; however, discrepancies have arisen regarding biological and technical issues. The aim of this study was to standardize an operating procedure and data analysis for identification of CPK by MALDI-TOF MS. To evaluate this approach, a series of 162 K. pneumoniae isolates (112 CPK and 50 non-CPK) were processed in the MALDI BioTyper system (Bruker Daltonik, Germany) following a standard operating procedure. The study was conducted in two stages; the first is denominated the "reproducibility stage" and the second "CPK identification." The first stage was designed to evaluate the biological and technical variation associated with the entire analysis of CPK and the second stage to assess the final accuracy of MALDI-TOF MS for the identification of CPK. Therefore, we present an improved MALDI-TOF MS data analysis pipeline using neural network analysis implemented in Clover MS Data Analysis Software (Clover Biosoft, Spain) that is designed to reduce variability, guarantee interlaboratory reproducibility, and maximize the information selected from the bacterial proteome. Using the random forest (RF) algorithm, 100% of CPK isolates were correctly identified when all the peaks in the spectra were selected as input features and total ion current (TIC) normalization was applied. Thus, we have demonstrated that real-time direct tracking of CPK is possible using MALDI-TOF MS.

Occurrence of the p019 Gene in the blaKPC-Harboring Plasmids: Adverse Clinical Impact for Direct Tracking of KPC-Producing Klebsiella pneumoniae by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry.

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been used for the direct detection of KPC-producing isolates by analysis of the 11,109 Da mass peak representing the P019 protein. In this study, we evaluate the presence of the 11,109 Da mass peak in a collection of 435 unduplicated Klebsiella pneumoniae clinical isolates. The prevalence of the P019 peak in the blaKPC K. pneumoniae isolates was 49.2% (32/65). The 11,109 Da mass peak was not observed in any of the other carbapenemase (319) or noncarbapenemase producers (116). Computational analysis of the presence of the p019 gene was performed in the aforementioned carbapenemase-producing K. pneumoniae isolates fully characterized by whole-genome sequencing (WGS) and in a further collection of 1,649 K. pneumoniae genomes included in EuSCAPE. Herein, we have demonstrated that the p019 gene is not exclusively linked to the pKpQil plasmid but that it is present in the following plasmids: IncFIB(K)/IncFII(K)/ColRNAI, IncFIB(pQil), IncFIB(pQil)/ColRNAI, IncFIB(pQil)/IncFII(K), IncFIB(K)/IncFII(K), and IncX3. In addition, we have proven the independent movement of the Tn4401 and the ISKpn31, of which the p019 gene is a component. The absence of the p019 gene was obvious in Col440I, Col(pHAD28), IncFIB(K)/IncX3/IncFII(K), and IncFIB(K)/IncFII(K) plasmids. In addition, we also observed another plasmid in which neither Tn4401 nor ISKpn31 was found, IncP6. In the EuSCAPE, the occurrence of p019 varied from 0% to 100% among the different geographical locations. The adverse clinical impact of the diminished prevalence of the p019 gene within the plasmid encoding KPC-producing Klebsiella pneumoniae puts forward the need for reconsideration when applying this technique in a clinical setting.

Multicenter Performance Evaluation of MALDI-TOF MS for Rapid Detection of Carbapenemase Activity in Enterobacterales: The Future of Networking Data Analysis With Online Software.

In this study, we evaluate the performance of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for rapid detection of carbapenemase activity in Enterobacterales in clinical microbiology laboratories during a multicenter networking validation study. The study was divided into three different stages: "software design," "intercenter evaluation," and "clinical validation." First, a standardized procedure with an online software for data analysis was designed. Carbapenem resistance was detected by measuring imipenem hydrolysis and the results were automatically interpreted using the Clover MS data analysis software (Clover BioSoft, Spain). Second, a series of 74 genotypically characterized Enterobacterales (46 carbapenemase-producers and 28 non carbapenemase-producers) were analyzed in 8 international centers to ensure the reproducibility of the method. Finally, the methodology was evaluated independently in all centers during a 2-month period and results were compared with the reference standard for carbapenemase detection used in each center. The overall agreement rate relative to the reference method for carbapenemase resistance detection in clinical samples was 92.5%. The sensitivity was 93.9% and the specificity, 100%. Results were obtained within 60 min and accuracy ranged from 83.3 to 100% among the different centers. Further, our results demonstrate that MALDI-TOF MS is an outstanding tool for rapid detection of carbapenemase activity in Enterobacterales in clinical microbiology laboratories. The use of a simple in-house procedure with online software allows routine screening of carbapenemases in diagnostics, thereby facilitating early and appropriate antimicrobial therapy.

Implementation of MALDI-TOF Mass Spectrometry and Peak Analysis: Application to the Discrimination of Cryptococcus neoformans Species Complex and Their Interspecies Hybrids.

Matrix-assisted laser desorption-ionization/time of flight mass spectrometry (MALDI-TOF MS) has been widely implemented for the rapid identification of microorganisms. Although most bacteria, yeasts and filamentous fungi can be accurately identified with this method, some closely related species still represent a challenge for MALDI-TOF MS. In this study, two MALDI-TOF-based approaches were applied for discrimination at the species-level of isolates belonging to the Cryptococcus neoformans complex, previously characterized by Amplified Fragment Length Polymorphism (AFLP) and sequencing of the ITS1-5.8S-ITS2 region: (i) an expanded database was built with 26 isolates from the main Cryptococcus species found in our setting (C. neoformans, C. deneoformans and AFLP3 interspecies hybrids) and (ii) peak analysis and data modeling were applied to the protein spectra of the analyzed Cryptococcus isolates. The implementation of the in-house database did not allow for the discrimination of the interspecies hybrids. However, the performance of peak analysis with the application of supervised classifiers (partial least squares-discriminant analysis and support vector machine) in a two-step analysis allowed for the 96.95% and 96.55% correct discrimination of C. neoformans from the interspecies hybrids, respectively. In addition, PCA analysis prior to support vector machine (SVM) provided 98.45% correct discrimination of the three analyzed species in a one-step analysis. This novel method is cost-efficient, rapid and user-friendly. The procedure can also be automatized for an optimized implementation in the laboratory routine.

Precession modulation of the South Pacific westerly wind belt over the past million years.

The southern westerly wind belt (SWW) interacts with the Antarctic Circumpolar Current and strongly impacts the Southern Ocean carbon budget, and Antarctic ice-sheet dynamics across glacial-interglacial cycles. We investigated precipitation-driven sediment input changes to the Southeast Pacific off the southern margin of the Atacama Desert over the past one million years, revealing strong precession (19/23-ka) cycles. Our simulations with 2 ocean-atmosphere general circulation models suggest that observed cyclic rainfall changes are linked to meridional shifts in water vapor transport from the tropical Pacific toward the southern Atacama Desert. These changes reflect a precessional modulation of the split in the austral winter South Pacific jet stream. For precession maxima, we infer significantly enhanced rainfall in the southern Atacama Desert due to a stronger South Pacific split jet with enhanced subtropical/subpolar jets, and a weaker midlatitude jet. Conversely, we derive dry conditions in northern Chile related to reduced subtropical/subpolar jets and an enhanced midlatitude jet for precession minima. The presence of precessional cycles in the Pacific SWW, and lack thereof in other basins, indicate that orbital-scale changes of the SWW were not zonally homogeneous across the Southern Hemisphere, in contrast to the hemispherewide shifts of the SWW suggested for glacial terminations. The strengthening of the jet is unique to the South Pacific realm and might have affected winter-controlled changes in the mixed layer depth, the formation of intermediate water, and the buildup of sea-ice around Antarctica, with implications for the global overturning circulation and the oceanic storage of atmospheric CO2.

Consistently dated Atlantic sediment cores over the last 40 thousand years.

Rapid changes in ocean circulation and climate have been observed in marine-sediment and ice cores over the last glacial period and deglaciation, highlighting the non-linear character of the climate system and underlining the possibility of rapid climate shifts in response to anthropogenic greenhouse gas forcing. To date, these rapid changes in climate and ocean circulation are still not fully explained. One obstacle hindering progress in our understanding of the interactions between past ocean circulation and climate changes is the difficulty of accurately dating marine cores. Here, we present a set of 92 marine sediment cores from the Atlantic Ocean for which we have established age-depth models that are consistent with the Greenland GICC05 ice core chronology, and computed the associated dating uncertainties, using a new deposition modeling technique. This is the first set of consistently dated marine sediment cores enabling paleoclimate scientists to evaluate leads/lags between circulation and climate changes over vast regions of the Atlantic Ocean. Moreover, this data set is of direct use in paleoclimate modeling studies.

Reversed flow of Atlantic deep water during the Last Glacial Maximum.

The meridional overturning circulation (MOC) of the Atlantic Ocean is considered to be one of the most important components of the climate system. This is because its warm surface currents, such as the Gulf Stream, redistribute huge amounts of energy from tropical to high latitudes and influence regional weather and climate patterns, whereas its lower limb ventilates the deep ocean and affects the storage of carbon in the abyss, away from the atmosphere. Despite its significance for future climate, the operation of the MOC under contrasting climates of the past remains controversial. Nutrient-based proxies and recent model simulations indicate that during the Last Glacial Maximum the convective activity in the North Atlantic Ocean was much weaker than at present. In contrast, rate-sensitive radiogenic (231)Pa/(230)Th isotope ratios from the North Atlantic have been interpreted to indicate only minor changes in MOC strength. Here we show that the basin-scale abyssal circulation of the Atlantic Ocean was probably reversed during the Last Glacial Maximum and was dominated by northward water flow from the Southern Ocean. These conclusions are based on new high-resolution data from the South Atlantic Ocean that establish the basin-scale north to south gradient in (231)Pa/(230)Th, and thus the direction of the deep ocean circulation. Our findings are consistent with nutrient-based proxies and argue that further analysis of (231)Pa/(230)Th outside the North Atlantic basin will enhance our understanding of past ocean circulation, provided that spatial gradients are carefully considered. This broader perspective suggests that the modern pattern of the Atlantic MOC-with a prominent southerly flow of deep waters originating in the North Atlantic-arose only during the Holocene epoch.

Long-term immunovirogical effect and tolerability of a maraviroc-containing regimen in routine clinical practice.

OBJECTIVES: to analyze the long-term immunovirological effect and tolerability of a maraviroc-containing antiretroviral therapy in viraemic and pretreated HIV-infected patients with a high prevalence of hepatitis C virus (HCV) coinfection. METHODS: forty-six R5 HIV-infected patients (48% HCV-coinfected) started a maraviroc-containing antiretroviral regimen, including patients with multidrug resistant virus and patients after first virologic failure. A retrospective study was performed, analysing percentage of patients with undetectable viral load, mean CD4+ gain, liver enzymes, clinical events and treatment modification up to week 48. RESULTS: Raltegravir plus a boosted protease inhibitor was combined with maraviroc in 65.2% of the patients (mainly patients with multidrug resistant virus), while the coformulation lamivudine/abacavir was combined with maraviroc in 26.1% (all of them patients after first virologic failure). After 48 weeks on maraviroc-containing regimen, 96.3% of the patients had achieved undetectability and a mean CD4+ count increase of 151 cells/mm3 was observed. Liver enzymes did not increase along the follow up. One patient died after 24 weeks follow up due to heroin overdose. One patient developed a non-Hodgkin lymphoma after 36 weeks follow up, despite undetectable viral load and significant CD4+ increase was achieved (the only AIDS-defining event observed). Treatment modification was performed in 19.6% of the patients: 77.7% of them experienced a treatment simplification and only 1/46 suspended maraviroc. CONCLUSIONS: maraviroc-containing regimen is long-term effective and well tolerated in HIV-infected patients in routine clinical practice and in different clinical scenarios.