Biology subjects

Hartmann, A.

Publications and source records attributed to Hartmann, A..

13 recordsLinked to original sources

bioRxiv2026

Complex folding kinetics of multi-domain proteins disentangled with periodic forces by magnetic tweezers

Force spectroscopy enables direct investigation of the interplay between free energy and transition kinetics in proteins and nucleic acids. However, multi-domain proteins often display multiple intermediate structures with diverse stabilities and kinetics, making equilibrium conditions difficult to achieve and out-of-equilibrium experiments challenging to interpret. We introduce a single-molecule force spectroscopy assay using periodic forces and high-resolution magnetic tweezers to bridge different stabilities, selectively enhance intermediate populations, and rigorously analyze multi-domain protein folding kinetics at quasi-equilibrium. By applying well-defined periodic square force functions with tunable steady states, we first validate our framework on the two-state folder {lambda}6-85, demonstrating that periodic force experiments can reproduce equilibrium kinetics. Extending this approach to the multi-domain protein mimic (Protein L), we show that tuning force, frequency, and amplitude enhances populations of distinct intermediate states. Finally, we dissect the entangled states of the hybrid two-domain protein {lambda}-L, where a 100-fold difference in domain kinetics precludes equilibrium analysis, by expanding from a two-state to a three-state periodic force protocol to direct intermediate populations. Our assay and analysis framework open new possibilities for deciphering complex multi-domain folds and their multi-dimensional folding pathways.

biophysics↗

bioRxiv2026

Multi-modal benchmarking of the Ultima UG100 and Illumina NovaSeq sequencing platforms using clinically relevant FFPE tissues

Emerging high-throughput sequencing technologies promise lower costs and higher scalability, yet their performance on archival clinical samples remains poorly characterized. Here, we benchmarked Ultima Genomics UG100 against Illumina Novaseq platforms across single-nuclei RNA-seq (snRNA-seq), whole-transcriptome (WTS), whole-exome (WES), and whole-genome sequencing (WGS) using FFPE tissues from oncologic and immune-mediated diseases. Across matched samples, we systematically assessed data quality, coverage profiles, error spectra, variant concordance and transcriptomic reproducibility. UG100 produced highly comparable results to Illumina, capturing key oncogenic and immune-related transcripts, accurately resolving cellular composition in snRNA-seq, and maintaining sensitivity for lowly expressed genes, despite characteristic insertion-biased indels and modest differences in multi-mapping reads. Discrepancies were subtle, largely limited to pseudogene and non-coding transcripts, and did not affect pathway-level conclusions. Ultima UG100 platform prioritized high precision and reduced low-frequency artifacts, offering a cleaner but more conservative variant-calling profile compared to the more sensitive, yet noisier, Illumina/DRAGEN workflow. This multimodal, clinically oriented assessment provides the first comprehensive evaluation of UG100, demonstrating its translational utility in population-scale genomics, and highlighting the potential for emerging sequencing technologies to lower the cost of biomedical research and clinical diagnostics.

genomics↗

bioRxiv2024

TACSTD2 expression marks the early transition to colon adenomas

This study aimed to address new molecular events occurring in precancerous stages of colorectal cancer (CRC) by integrated analysis of gene expression data and DNA methylation profiles. Whole-transcriptome sequencing analysis was performed on 16 fresh frozen colorectal adenoma and matched mucosa specimens along with validation of candidates in an independent cohort of 20 fresh frozen paired adenoma and adjacent mucosa tissues as well as eight independent public datasets (335 cases). Genome-wide methylation profiles were determined for 5 adenoma pairs and confirmed by pyrosequencing on 20 tissue pairs used for validation. Functional analysis was performed in vitro and in vivo using the inflammation-associated azoxymethane/dextran sodium sulfate (AOM/DSS) and the sporadic colorectal carcinogenesis (six AOM injections) mouse models as well as ApcMin/+ mice. Candidates were investigated by immunohistochemical staining of human adenomas and early-stage (pT1) CRC tumors. A total of 1,917 differentially expressed genes and 148,191 differentially methylated CpG sites were detected in adenomas compared with adjacent mucosa samples. Based on the transcriptome data and relevance to CRC, TACSTD2, MMP7, MMP1, CLDN2, CLDN1, and ETV4, were selected for further validation. TACSTD2 promoter hypomethylation in adenoma tissues was validated in 20 additional tissue pairs and corresponded with increased TACSTD2 expression. TACSTD2 was also overexpressed in an in vitro transformation model of human colonic epithelial cells. The TACSTD2 protein TROP2 was elevated in human adenomas, pT1 tumors, and in murine adenomas, while it was absent in the unaffected adjacent mucosa. TROP2 overexpression might trigger the development of precancerous lesions and could help identify early transformation foci in colon biopsies. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/620817v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1f23753org.highwire.dtl.DTLVardef@10e6abeorg.highwire.dtl.DTLVardef@181f500org.highwire.dtl.DTLVardef@fc0d38_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Elucidation and functional characterization of natural sweetener biosynthesis in hortensia species

Among the various coumarins found in Hydrangea species, the bioactive dihydroisocoumarin known as phyllodulcin (PD) stands out as a non-caloric, high-intensity sweetener, which is up to 800 times sweeter than sucrose. Additionally, PD possesses notable medicinal properties, including antifungal, anti-ulcer, and anti-inflammatory effects. PD also plays several plant-specific roles, such as defending against phytopathogens, responding to abiotic and biotic stresses and regulating hormones. However, the biological function and biosynthetic pathway of PD in Hydrangea remain unexplored. This study employs targeted metabolomic and transcriptomic approaches to uncover the regulatory mechanisms and identify potential candidate genes involved in the biosynthesis of PD. 14 out of 182 different Hydrangea accessions, exhibiting varying levels of PD, were selected for detailed analysis. Accessions of H. macrophylla with high PD levels displayed distinct metabolite profiles compared to those with low PD concentrations. Specifically, pathways involving caffeic acid, ferulic acid, and their derivatives, such as scopolin, scopoletin, esculetin, and fraxetin, were predominant in accessions with low PD concentrations. Conversely, the metabolism of phenylalanine, umbelliferone, p-coumaric acid, naringenin, resveratrol, and Thn C was more active in accessions containing PD. Correlation analysis between PD and these metabolites offered valuable insights into their interrelationships. Transcriptome analysis revealed specific genes involved in phenylpropanoid biosynthesis, flavonoid biosynthesis, and stilbene biosynthesis pathways that are crucial for PD biosynthesis. Moreover, the identification of cyclase and ketoreductase genes, which were up regulated in accessions with high PD, provided further understanding of the biosynthetic pathway leading to PD. Finally, based on metabolite levels and gene expression data, a hypothetical pathway from resveratrol to Thn C was proposed, suggesting its potential involvement in PD biosynthesis. HighlightThe metabolic and transcriptomic analysis led to the identification of specific metabolites and genes that are involved in the biosynthesis of dihydrisocoumarin.

plant biology↗

bioRxiv2024

Closing the gap in the clinical adoption of computational pathology: a standardized, open-source framework to integrate deep-learning algorithms into the laboratory information system

Digital pathology (DP) has revolutionized cancer diagnostics, allowing the development of deep-learning (DL) models supporting pathologists in their daily work and contributing to the improvement of patient care. However, the clinical adoption of such models remains challenging. Here we describe a proof-of-concept framework that, leveraging open-source DP software and Health Level 7 (HL7) standards, allows the integration of DL models in the clinical workflow. Development and testing of the workflow were carried out in a fully digitized Italian pathology department. A Python-based server-client architecture was implemented to interconnect the anatomic pathology laboratory information system (AP-LIS) with an external artificial intelligence decision support system (AI-DSS) containing 16 pre-trained DL models through HL7 messaging. Open-source toolboxes for DL model deployment, including WSInfer and WSInfer-MIL, were used to run DL model inference. Visualization of model predictions as colored heatmaps was performed in QuPath. As soon as a new slide is scanned, DL model inference is automatically run on the basis of the slides tissue type and staining. In addition, pathologists can initiate the analysis on-demand by selecting a specific DL model from the virtual slides tray. In both cases the AP-LIS transmits an HL7 message to the AI-DSS, which processes the message, runs DL model inference, and creates the appropriate type of colored heatmap on the basis of the employed classification model. The AI-DSS transmits model inference results to the AP-LIS, where pathologists can visualize the output in QuPath and/or directly from the virtual slides tray. The developed framework supports multiple DL toolboxes and it is thus suitable for a broad range of applications. In addition, this integration workflow is a key step to enable the future widespread adoption of DL models in pathology diagnostics.

pathology↗

bioRxiv2024

Coexistence of asynchronous and clustered dynamics in noisy inhibitory neural networks

A regime of coexistence of asynchronous and clustered dynamics is analyzed for globally coupled homogeneous and heterogeneous inhibitory networks of quadratic integrate-and-fire (QIF) neurons subject to Gaussian noise. The analysis is based on accurate extensive simulations and complemented by a mean-field description in terms of low-dimensional next generation neural mass models for heterogeneously distributed synaptic couplings. The asynchronous regime is observable at low noise and becomes unstable via a sub-critical Hopf bifurcation at sufficiently large noise. This gives rise to a coexistence region between the asynchronous and the clustered regime. The clustered phase is characterized by population bursts in the{gamma} -range (30-120 Hz), where neurons are split in two equally populated clusters firing in alternation. This clustering behaviour is quite peculiar: despite the global activity being essentially periodic, single neurons display switching between the two clusters due to heterogeneity and/or noise.

neuroscience↗

bioRxiv2024

Triplex real-time PCR ZKIR-T assay for simultaneous detection of the Klebsiella pneumoniae species complex and identification of K. pneumoniae sensu stricto

Klebsiella pneumoniae species complex (KpSC) members, including the most important species K. pneumoniae (phylogroup Kp1 of the KpSC), are important opportunistic pathogens which display increasing rates of antimicrobial resistance worldwide. As they are widespread in food and the environment, there is a need for fast, sensitive and reliable methods to detect KpSC members in complex matrices. Previously, the ZKIR real-time PCR assay was developed to detect all KpSC members without distinction. Given that Kp1 is the clinically most significant phylogroup of the KpSC, here we aimed to simultaneously identify Kp1 while detecting all KpSC members. Three TaqMan probes were developed and used: the zkir P1 probe to detect phylogroups Kp1 to Kp5 and Kp7; the zkir P2 probe to detect phylogroup Kp6; and the Kp1 probe to specifically identify this phylogroup. The new assay was tested on a total of 95 KpSC and 19 non-KpSC strains from various sources, representing the different phylogroups as defined by whole genome sequencing. The results showed almost complete specificity, as the expected PCR results were obtained for 112 (98%) strains. The new triplex real-time PCR assay, called ZKIR-T, enables detection of all KpSC taxa while discriminating Kp1, which will be useful for rapid screening and to focus downstream analyses on chosen phylogroups of the KpSC. ImportanceThe pathogens of the Klebsiella pneumoniae species complex are widespread in food and animals and are amongst the main pathogens responsible for multidrug resistant infections in humans. In this study, we developed a highly sensitive detection assay that enables detection of this group of bacteria, with the simultaneous identification of the most common and clinically important species. This triplex one-reaction assay was shown to be highly sensitive and precise, enabling fast screening of varied samples for the presence of KpSC and K. pneumoniae sensu stricto.

microbiology↗

bioRxiv2023

Farewell to single-well: An automated single-molecule FRET platform for high-content, multiwell plate screening of biomolecular conformations and dynamics

Single-molecule FRET (smFRET) has become a widely used tool for probing the structure, dynamics, and functional mechanisms of biomolecular systems, and is extensively used to address questions ranging from biomolecular folding to drug discovery. Investigations by smFRET often require sampling of a large parameter space, for example, by varying one or more constituent molecular components in ten or more steps to reliably extract distances, kinetic rates, and other quantitative parameters. Confocal smFRET measurements, for example, which are amongst the widely used smFRET assays, are typically performed in a single-well format and measurements are conducted in a manual manner, making sampling of many experimental parameters laborious and time consuming. To address this challenge, we extend here the capabilities of confocal smFRET beyond single-well measurements by integrating a multiwell plate functionality into a confocal microscope to allow for continuous and automated smFRET measurements. We show that the multiwell plate assay is on par with conventional single-well smFRET measurements in terms of accuracy and precision yet enables probing tens to hundreds of conditions in a fully automized manner. We demonstrate the broad applicability of the multiwell plate assay towards DNA hairpin dynamics, protein folding, and competitive and cooperative protein-DNA interactions, revealing new insights that would be hard if not impossible to achieve with conventional single-well format measurements. The higher sampling density afforded by the multiwell plate format increases the accuracy of data analysis by at least 10-fold. We further showcase that the assay provides access to smFRET-based screening of drug-protein interactions. For the adaptation into existing instrumentations, we provide a detailed guide and open-source acquisition and analysis software. Taken together, the automated multiwell plate assay developed here opens up new possibilities to acquire high-content smFRET datasets for in-depth single-molecule analysis of biomolecular conformations, interactions, and dynamics.

biophysics↗

bioRxiv2022

Reliability and accuracy of single-molecule FRET studies for characterization of structural dynamics and distances in proteins

Single-molecule FRET (smFRET) has become an established tool to study biomolecular structure and dynamics in vitro and in live cells. We performed a worldwide blind study involving 19 labs to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems that undergo distinct conformational changes, we obtained an uncertainty of the FRET efficiency of less than {+/-} 0.06, corresponding to an interdye distance precision of [≤] 0.2 nm and accuracy of [≤] 0.5 nm. We further discuss the limits for detecting distance fluctuations with sensitivity down to [lsim] 10% of the Forster distance and provide guidelines on how to detect potential dye perturbations. The ability of smFRET experiments to simultaneously measure distances and avoid averaging of conformational dynamics slower than the fluorescence lifetime is unique for dynamic structural biology.

biophysics↗

bioRxiv2021

Chaperones Skp and SurA dynamically expand unfolded outer membrane protein X and synergistically disassemble oligomeric aggregates

Periplasmic chaperones Skp and SurA are essential players in outer membrane protein (OMP) biogenesis. They prevent unfolded OMPs from misfolding during their passage through the periplasmic space and aid in the disassembly of OMP aggregates under cellular stress conditions. However, functionally important links between interaction mechanisms, structural dynamics, and energetics that underpin both Skp and SurA association with OMPs have remained largely unresolved. Here, using single-molecule fluorescence spectroscopy, we dissect the conformational dynamics and thermodynamics of Skp and SurA binding to unfolded OmpX, and explore their disaggregase activities. We show that both chaperones expand unfolded OmpX distinctly and induce microsecond chain reconfigurations in the client OMP structure. We further reveal that Skp and SurA bind their substrate in a fine-tuned thermodynamic process via enthalpy-entropy compensation. Finally, we observed synergistic activity of both chaperones in the disaggregation of oligomeric OmpX aggregates. Our findings provide an intimate view into the multi-faceted functionalities of Skp and SurA and the fine-tuned balance between conformational flexibility and underlying energetics in aiding chaperone action during OMP biogenesis.

biophysics↗

bioRxiv2020

Direct visualization of four diffusive LexA states controlling SOS response strength during antibiotic treatment

In bacteria, the key mechanism governing mutation, adaptation and survival upon DNA damage is the SOS response. Through autoproteolytic digestion triggered by single-stranded DNA caused by most antibiotics, the transcriptional repressor LexA controls over 50 SOS genes including DNA repair pathways and drivers of mutagenesis. Efforts to inhibit this response and thereby combat antibiotic resistance rely on a broad understanding of its behavior in vivo, which is still limited. Here, we develop a single-molecule localization microscopy assay to directly visualize LexA mobility in Escherichia coli and monitor the SOS response on the level of transcription factor activity. We identify four diffusive populations and monitor their temporal evolution upon ciprofloxacin-induced continuous DNA damage. With LexA mutants, we assign target bound, non-specifically DNA bound, freely diffusing and cleaved repressors. We develop a strategy to count LexA in fixed cells at different time points after antibiotic stress and combine the time-evolution of LexA sub-populations and the repressors overall abundance. Through fitting a detailed kinetic model we obtain in vivo synthesis, cleavage and binding rates and determined that the regulatory feedback system reaches a new equilibrium in [~]100 min. LexA concentrations showed non-constant heterogeneity during SOS response and designate LexA expression, and thereby regulation of downstream SOS proteins, as drivers of evolutionary adaptation. Even under low antibiotic stress, we observed a strong SOS response on the LexA level, suggestion that small amounts of antibiotics can trigger adaptation in E. coli.

biophysics↗

bioRxiv2019

Panel Sequencing in Uterine Leiomyomas identifies Missense Mutations associated with immunohistochemical Fumarate Hydratase (FH)-Loss

ABSTRACTUterine leiomyomas (ULs) constitute a considerable health burden in the general female population. The fumarate hydratase (FH) deficient subtype is found in up to 1.6% and can occur in hereditary leiomyomatosis and renal cell carcinoma (HLRCC) syndrome.We sequenced 13 FH deficient ULs from a previous immunohistochemical screen using a targeted panel and identified biallelic FH variants in all. In eight, we found a FH point mutation (two truncating, six missense) with evidence for loss of the second allele. Variant allele-frequencies in all cases with a point mutation pointed to somatic variants. Spatial clustering of the identified missense variants in the lyase domain indicated altered fumarase oligomerization with subsequent degradation as explanation for the observed FH deficiency. Biallelic FH deletions in five tumors confirm the importance of copy number loss as mutational mechanism.By curating all pathogenic FH variants and calculating their population frequency, we estimate a carrier frequency of up to 1/2,563. Comparing with the prevalence of FH deficient ULs, we conclude that most are sporadic and estimate 2.7 - 13.9% of females with an FH deficient UL to carry a germline FH variant.Further prospective tumor/normal sequencing studies are needed to develop a reliable screening strategy for HLRCC in women with ULs.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pathology↗

bioRxiv2018

The consensus molecular classification of muscle-invasive bladder cancer

Muscle-Invasive Bladder Cancer (MIBC) is a molecularly diverse disease with heterogeneous clinical outcomes. Several molecular classifications have been proposed, yielding diverse sets of subtypes, which hampers the clinical implications of such knowledge. Here, we report the results of a large international effort to reach a consensus on MIBC molecular subtypes. Using 1750 MIBC transcriptomes and a network-based analysis of six independent MIBC classification systems, we identified a consensus set of six molecular classes: Luminal Papillary (24%), Luminal Non-Specified (8%), Luminal Unstable (15%), Stroma-rich (15%), Basal/Squamous (35%), and Neuroendocrine-like (3%). These consensus classes differ regarding underlying oncogenic mechanisms, infiltration by immune and stromal cells, and histological and clinical characteristics. This consensus system offers a robust framework that will enable testing and validating predictive biomarkers in future clinical trials.

cancer biology↗