Cholesterol is a central building block in biomembranes,whereit induces orientational order, slows diffusion, renders the membranestiffer, and drives domain formation. Molecular dynamics (MD) simulationshave played a crucial role in resolving these effects at the molecularlevel; yet, it has recently become evident that different MD forcefields predict quantitatively different behavior. Although easilyneglected, identifying such limitations is increasingly importantas the field rapidly progresses toward simulations of complex membranesmimicking the in vivo conditions: pertinent multicomponent simulationsmust capture accurately the interactions between their fundamentalbuilding blocks, such as phospholipids and cholesterol. Here, we definequantitative quality measures for simulations of binary lipid mixturesin membranes against the C–H bond order parameters and lateraldiffusion coefficients from NMR spectroscopy as well as the form factorsfrom X-ray scattering. Based on these measures, we perform a systematicevaluation of the ability of commonly used force fields to describethe structure and dynamics of binary mixtures of palmitoyloleoylphosphatidylcholine(POPC) and cholesterol. None of the tested force fields clearly outperformsthe others across the tested properties and conditions. Still, theSlipids parameters provide the best overall performance in our tests,especially when dynamic properties are included in the evaluation.The quality evaluation metrics introduced in this work will, particularly,foster future force field development and refinement for multicomponentmembranes using automated approaches. Notably, simulations using CHARMM36, Lipid17, andSlipids can these days be set up for multiple simulation engines withthe CHARMM-GUI online tool; this decreases greatly the manual workneeded to run complex membrane simulations.37The traditional protein force fields CHARMM,42 This approach has been useful for finding the best force fieldsto describe the headgroups of phosphatidylcholine (PC),43 phosphatidylserine (PS),41 phoshatidylethanolamine(PE),42 and phosphatidylglycerol (PG) lipids;42 to evaluate and improve membrane interactionswith ions45 and small molecules;46 and to find simulationparameters predicting most realistic packing properties of membranes.48 Furthermore, quantitative quality measures based on the C–Hbond order parameters have been recently defined and used to ranksimulations in the NMRlipids Databank.48 However, such automatic quality evaluation is limited to simulationsfor which experimental data at the corresponding composition and temperatureare available. Because simulations mimicking all experimental compositionsfor multicomponent membranes are often tedious to produce, qualityevaluation of mixed lipid bilayers is not yet fully automatized inthe NMRlipids Databank.While simulating complex membranes with CHOL has become arelativelystraightforward task, estimating the trustworthiness of MD simulationsremains a challenge, especially as the complexity and number of membranecomponents increase. Our earlier work has demonstrated that the conformationalensembles of lipids from an MD simulation can be evaluated againstthe C–H bond order parameters from NMR experiments.49 we focus here on the acyl chains;these are expected to play a larger role than the headgroup in CHOL-inducedlateral membrane heterogeneity. We also evaluate the dependence oflateral diffusion coefficients on CHOL against pulsed field gradient(PFG) NMR experiments51 using the recent theoreticalframework that allows a quantitative comparison with experiment byeliminating finite-size effects in MD simulations.53 With the structural and dynamic comparisons established, we thenestimate the quality of the four popular force fields at differentCHOL concentrations. While we focus here on a POPC–CHOL mixture,we expect our results to set guidelines for future efforts to validateintermolecular interactions for other phosphatidylcholine–cholesterolmixtures, as well as any binary or multicomponent systems.Here, we demonstrate how simulationsof binary palmitoyloleoylphosphatidylcholine–cholesterol(POPC–CHOL) mixtures can be evaluated against experimentalNMR spectroscopy and X-ray scattering data by interpolating throughmultiple CHOL concentrations. As the effect of CHOL on lipid headgroup(and its independence from acyl chain ordering) has been discussedpreviously,22.155 This avoids the precipitation of CHOL crystallites at high concentrations,56 yielding non-phase-separated samples up to 50mol % CHOL content. Lipids, purchased from Avanti Polar Lipids , were used as dry powders without any further purification.All other chemicals were obtained in pro analysis quality from Lactan. The data were obtained at the EMBL BioSAXS beamline(Hamburg) using 20 keV photons at T = 300 Kand analyzed in terms of the scattering density profile (SDP)-GAPmodel described in refs . These data are also added in theNMRlipids databank , and are available using the NMRlipidsprotocols described in ref (Fullyhydrated multilamellar vesicles (MLVs), composed of POPC and CHOLwith the latter present at 0–50 mol % with 5 mol % increments,were prepared for small-angle X-ray scattering (SAXS) experimentsusing rapid solvent exchange as described previously. in refs  and 58)55 This ain refs . The memd in ref .2.225 Amber-compatibleSlipids30 with its 2020 update,31 Amber-compatible Lipid17,27 and all-atom-OPLS-compatibleMacRog.35 To eliminate the finite-size effects due to periodicboundary conditions from lateral diffusion coefficients of lipids,we performed all simulations in three sizes . The number of POPC molecules was kept constant acrossthe different CHOL concentrations. All membranes were solvated by50 water molecules per lipid (POPC or CHOL). The small membranes (with64 lipids) were first generated using CHARMM-GUI and equilibratedusing the standard protocols for CHARMM36, Slipids, and Lipid17, forwhich inputs are readily available from CHARMM-GUI.37 Then, the atomic coordinates were replicated in the membrane planeto create the 4- and 16-fold larger simulation systems ,DOI: 10.5281/zenodo.7022749 (Slipids), DOI: 10.5281/zenodo.6992065(Lipid17), and DOI: 10.5281/zenodo.7061800 (MacRog). All simulationswere added to the NMRlipids Databank48 andtheir ID numbers are listed in Table S2. These ID numbers can be used to access the raw simulation dataand experimental data linked to each simulation using the NMRlipidsprotocols described in ref 2.32.3.148 were used. Similarly to the experimental X-ray scatteringdata, the membrane thickness was defined as twice the distance fromthe electron density maximum to the membrane center. Locations ofmaxima were extracted by the findpeaks functionin Matlab after smoothening the electron density data with the smooth function  in Matlab.Area per phospholipid was obtained by dividing the area of the bilayer(area of the simulation box) by the number of phospholipids in oneleaflet.The C–Hbond order parameters, form factors, and electron density profiles,automatically calculated by the NMRlipids Databank,2 (CH3) groups in the POPC acyl chains were averaged.These groups rotate freely and thus the order parameters are essentiallyidentical for both  hydrogens in experiments and simulations.An exception to this are the hydrogens bound to the second carbonin the oleate chain; they lack rotational averaging in both simulationsand experiments and were thus treated separately in our analyses.The C–H order parameters for the POPC headgroup are shown separatelyfor all CH2 groups, i.e., no averaging was performed.To simplify the interpolation of order parameter datato intermediate CHOL concentrations ,C–H bond order parameters of the 2 (3) hydrogens in CH2.3.2DPBC fromsimulations performed using periodic boundary conditions (PBC) wereextracted from mean squared displacement (MSD) data calculated forlipid centers of mass after the drift of their host leaflet was eliminatedwith the gmx msd tool. The MSD data were fitwith a straight line in the lag time (Δ) interval between 10and 100 ns asLateral diffusion coefficients L) were fitted withD∞ is the lateral diffusion coefficient in an infinite system, h is the hydrodynamic thickness of the membrane, kB is the Boltzmann constant, T is the temperature, H is half the thickness ofthe water layer, m and μf are shear viscositiesof the membrane and the fluid (water), respectively.53 Thus, the fit of DPBC values calculatedfrom the simulation as a function of simulation box size L has two free parameters, namely, D∞ and μm, both of which are free of finite-size effectsand can thus be compared to experiment. The interleaflet frictioncoefficient does not appear in 53 The water viscosity value of μf = 0.3228 mPa swas interpolated to 298 K from the values for CHARMM TIP3P in ref  Lz) were taken from the final configurationof each simulation. Lz was needed only in the calculation of H (see below).Membrane thickness h was obtained as described in“Structural properties” above. As h and H = (Lz – h)/2 are constants in The diffusion coefficients extractedfrom the three simulation box sizes  but withthe scatteredInterpolant function in Matlabbased on Delaunay triangulation.66 Linear1D interpolation with the interp1 functionin Matlab was used for the CHOL dependence of the first and secondform factor minima locations and diffusion coefficients. These interpolationswere then used to calculate deviations (in %) from experimental values across CHOL concentrations to quantifythe quality of the lipid force fields. For the 2D matrices, the absolutevalues of the differences between the matrices from simulations andexperiments were first calculated. The averages of differences overthe carbon atoms in the acyl chain (order parameters) or across theentire z coordinate in the simulation (density profiles)were then calculated. This resulted in 1D deviation vectors as a functionof the CHOL concentration. For diffusion coefficients and form factorminima , the absolute value of the difference of the interpolated1D vectors of simulation and experimental data was calculated to providedeviation as a function of CHOL concentration. All of these 1D vectorswere normalized by dividing them by the experimental values to providerelative deviations in % between a simulation and experiments as afunction of CHOL concentration. For C–H bond order parameters,the deviation matrices between simulations and experiments were alsoused to illustrate the quality of simulations.To ease the evaluation ofsimulations against experimental data with nonmatching CHOL concentrations,we interpolated the effect of CHOL in simulations and experimentsfor CHOL concentrations ranging from 0 to 46 mol %. Two-dimensional(2D) matrices were created by interpolation for the oleate and palmitatechain order parameters (as a function of carbon atoms in the acylchains and CHOL concentration) using the 33.167 which is suggestedto play a critical role in the phase behavior of PC–CHOL mixtures.6 Consequently, the correct CHOL-induced orderingis expected to be a necessary condition for a force field used tounderstand lipid–CHOL phase behavior. The CHOL-induced orderingcan be experimentally quantified by measuring the C–H bondorder parameters using 13C or 2H NMR, and theresults can also be directly compared to MD simulations.39 Simulations generally show some CHOL-inducedordering, but the order parameter values often deviate from the experimentalones at high CHOL concentrations.67 Furthermore,it has not been clear how accurately different force fields capturethe details of lipid–CHOL interactions and which force fieldwould give most realistic results for simulations of complex mixtures,where such interactions play critical roles.CHOL is known to induce order in lipid membranesby increasing the fraction of anti conformations in the acyl chainsof phospholipids,13C NMR experimentsmeasured from POPC–CHOL mixtures with CHOL concentrations rangingbetween 0 and 60 mol %.67 To this end,we first interpolated order parameter maps as a function of the acylchain carbon number and CHOL concentration for both simulations andexperiments. These maps were then subtracted to obtain deviation mapsbetween the simulations and experiments. The deviation maps of differentforce fields are shown for the palmitate (top row) and oleate (bottomrow) chains of POPC in Figures S6 and S7 for the palmitateand oleate chains, respectively.Here, we evaluatethe CHOL-induced ordering in state-of-the-art force fields againstC–H bond order parameter data from Figures S6 and S7) as a substantial increasein the absolute values of acyl chain C–H bond order parametersupon addition of CHOL. The deviations mapped in In the simulations with all tested force fieldsas well as in experiments,the CHOL-induced ordering is manifested in the original profiles  model or its combination with MD simulations.70 To complementthe evaluation of CHOL-induced ordering against NMR order parameters,we also measured the X-ray form factors from POPC–CHOL mixturesat systematically increasing CHOL concentrations. Scattering intensitiesfrom experiments are shown in Figures S1 and S2, form factors from experiments and simulations in Figure S3, and density profiles in Figure S4.CHOL-inducedordering straightens the acyl chains, which leads to membrane thickening.While acyl chain order and membrane thickness are well correlated,The effect of CHOL on the structural properties ofbilayers is compared between the SDP model  and MD simulation results in 2 Lipid17has the largest APL across the entire CHOL concentration range. MacRogalso has a large APL for pure POPC, but the partial area of CHOL isnegative until 30 mol % concentration, indicating a particularly strongcondensation effect. The profiles for Slipids and CHARMM36 are verysimilar, with a small or zero partial area of CHOL until a concentrationof 20 mol %.The dependence of the area per phospholipid (APL)on CHOL concentrationfollows the trends in thickness inversely in general  as a function of CHOL concentrationto create two-dimensional electron density maps , suggesting more uniform membrane structure than any MD simulation.However, system size plays a role here as undulations smear out thedensity profile features with increasing simulation box size, as demonstratedin Figure S13 by the density maps calculatedfor the CHARMM36 simulations in three sizes. Still, even in the smallestsystem, the band intensities are less localized than those in theSDP model. This might indicate different elastic properties betweensimulation and experiment, but we cannot fully exclude the role ofmodels used to interpret the scattering data.For a more detailed comparison of membrane structure,we interpolatedthe changes in electron density profiles along the membrane normalS4 as a f48 To avoid the effects fromsimulation system sizes, we thus interpolated the locations of thefirst two minima in the form factors over the entire studied rangeof CHOL concentrations  which complicates their direct comparisonwith experimental data. Nevertheless, the minima in X-ray form factorsare independent of the simulation box size and correlate with membranedimensions.3.351 The comparison between lateraldiffusion coefficients extracted from simulation and experiment hasbeen limited due to a box size dependence observed in simulationsperformed using periodic boundary conditions (PBCs).71 Here, we tackle this issue byperforming simulations with three system sizes, which allows extrapolationof the results to an infinite system with the theoretical descriptiondeveloped by Vögele and Hummer.53 The size dependenceof phospholipid lateral diffusion from simulations together with thefit of Figure S9, whereas the CHOL dependenciesof these values in systems with different sizes are shown in Figure S10. The PBC-corrected lateral diffusioncoefficients of POPC are shown in the top panel of 1H pulsed field gradient NMR diffusion measurementson label-free macroscopically aligned bilayers.51Apart from the ordering effect on the bilayerstructure, CHOL is also known to make bilayers stiffer and less dynamic.Table S1). The PBC-corrected diffusion coefficient valueswith shorter cutoff, shown in the top panel of The lipid force fields again show significantlydifferent behaviors.Lipid17 and CHARMM36 show too fast dynamics for pure POPC, and theslowdown induced by CHOL is exaggerated compared to experiment. Diffusionin MacRog is generally too slow. In contrast, Slipids provides anessentially quantitative agreement with experiment across the studiedCHOL concentrations and thus significantly outperforms the other forcefields in terms of lateral dynamics. Interestingly, there is no correlationbetween the deviations from experiments and the structural propertiesdescribed earlier. To investigate if the differences in lateral diffusioncoefficients could be explained by different Lennard-Jones (LJ) cutoffvalues, we repeated simulations at 0 and 47 mol % CHOL for Slipidsusing a shorter cutoff of 0.9 nm  using interpolated datafor the form factor minima, the order parameters of the two acyl chains,and the diffusion coefficients. The quality evaluations are shownin The quality evaluations reveal that Slipids providesthe overallbest agreement with experiment, yet its quality decreases slightlyat higher CHOL concentrations. Lipid17 provides a slightly betteragreement with experiment above ∼30 mol % CHOL than Slipidsbut exhibits major deviation from experiments at low CHOL concentrations.MacRog performs relatively well at low CHOL concentrations, but itsquality deteriorates significantly upon addition of CHOL. The deviationfor CHARMM36 is significant at all CHOL concentrations.467 suggestedthe same conclusion for the historically relevant Berger/Höltjeforce field parameters75 that were not included in thiswork.The tested all-atom forcefields captured the most important generaleffects of CHOL on POPC membrane properties: increased acyl chainordering, concomitant increase in bilayer thickness, and reduced lateraldiffusion rate of phospholipids, i.e., features associated with theliquid-ordered phase. However, a quantitative comparison reveals differencesbetween force fields and their qualities evaluated against NMR andX-ray scattering data. Comparison with NMR order parameters and X-rayscattering form factors proposes that simulations reproduce experimentalresults until up to 20 mol % CHOL, but overestimate theacyl chain ordering and membrane thickness after further additionof CHOL. An apparent exception to this is the Lipid17 force field,yet its seemingly better agreement with experiments results from compensationof the initially (at low CHOL concentrations) underestimated acylchain order by the overly strong response to CHOL addition. In conclusion,a unified picture emerging from comparison with NMR and X-ray scatteringdata suggests that all of the tested force fields overestimate theCHOL-induced ordering effect, particularly above 20 mol % of CHOL.A previously published comparison77 However, suchstructures seem to only be present at temperatures below the maintransition temperature of the lipid with saturated chains.78 As the main transition temperature of POPC liesbelow 273 K, hexagonal packing is not expected, and our findings areconsistent with the earlier studies.Notably, no phase separation or domain formation was evidentinour simulations. This differs from mixtures containing lipids withsaturated acyl chains such as DPPC, which were recently found to containhexagonally packed substructures.79 or (ii)CHOL having a diminishing partial area, meaning that a certain amountof CHOL could be added to a phospholipid bilayer without effectingits total area .80 Atthe physiological CHOL concentrations in the range from 0 to 30 mol%, only MacRog predicts negative partial area for CHOL, while CHARMM36predicts zero partial area, and Slipids and Lipid17 predict smallpositive partial areas. Considering that Slipids and Lipid17 performbest in our quality evaluation against experiments, yet still slightlyoverestimating the CHOL condensing effect, our results suggest thatCHOL has a positive but small partial area.Besides the CHOL-inducedordering, effects on membrane propertieshave been discussed also in terms of (i) the CHOL condensing effect,which refers to a decrease in the area per phospholipid upon the additionof CHOL ,81 Slipids isoverall closest to experiments among the parameters tested here, andis therefore probably the best choice for studies where phospholipid–CHOLinteractions play a major role. Nevertheless, all tested parameterscapture the qualitative effects of CHOL on POPC membrane propertiesrelatively well and differences between force fields are clearly smallerthan, for example, in the case of PC–PS lipid mixtures.47 Therefore, the quality of the force field selectedfor other molecules, such as proteins, sugars, drugs, or lipids otherthan phosphatidylcholine, and the force field compatibility mightbe more relevant decisive factors for simulations of complex systems.Finally, it must be noted that while all simulations were performedwith their suggested simulation parameters, the different simulationengines might provide slightly different behavior.36 This is especially true for the Lipid17 and CHARMM36 forcefields, which were originally not parametrized using GROMACS. Forexample, the overcondensation observed for CHARMM36 in this work resemblesearlier findings on the differences between simulation engines forCHOL-free membranes.36 We used GROMACShere for all simulations due to its popularity and compatibility withall tested force fields. Unfortunately, a comparison of results obtainedwith different simulation engines is beyond the scope of this work.Moreover, since the observed differences probably emerge from differencesin the handling of Lennard-Jones cutoffs, they are likely to be eliminatedin the near future by the emergence of force fields benefiting fromLJ-PME.85Considering alsolateral dynamics and previous evaluation of rotationaldynamics against NMR data,48 beyond individual systems: this enables the automatic rankingof not only lipid mixtures but also membranes mixed with other moleculessuch as ions. Such tools will strongly support the emerging endeavorsfor automatic improvement of force field parameters.47Our results demonstrate that quality evaluation of lipid mixturesimulations against experimental NMR and X-ray scattering data givesconsistent results for how accurately force field parameters captureintermolecular interactions. The interpolation approach introducedhere extends the NMRlipids Databank quality metrics


Akkermansia muciniphila), and the most affected metabolic pathways included a group of interconnected amino acids, bile acid conjugation, glucose homeostasis, and energy production. Highly correlated metabolic changes were observed between lumen and serum metabolism, supporting their significant interactions. Despite a small sample size, this study explored the largely uncharacterized microbial and metabolic events in an immunosuppressed environment and demonstrated that early changes in metabolic activities can have significant implications that may serve as antecedent biomarkers of immune activation or quiescence. To understand the intricate relationships among gut microbiome, metabolic activities, and immune cells in an immune suppressed environment is a prerequisite for developing strategies to monitor and optimize alloimmune responses that determine transplant outcomes.Intrinsic metabolism shapes the immune environment associated with immune suppression and tolerance in settings such as organ transplantation and cancer. However, little is known about the metabolic activities in an immunosuppressive environment. In this study, we employed metagenomic, metabolomic, and immunological approaches to profile the early effects of the immunosuppressant drug tacrolimus, antibiotics, or both in gut lumen and circulation using a murine model. Tacrolimus induced rapid and profound alterations in metabolic activities within two days of treatment, prior to alterations in gut microbiota composition and structure. The metabolic profile and gut microbiome after seven days of treatment was distinct from that after two days of treatment, indicating continuous drug effects on both gut microbial ecosystem and host metabolism. The most affected taxonomic groups are Clostriales and Verrucomicrobiae (i.e.,  The intrinsic metabolism is a major regulator of the immune environment, including metabolic activities associated with immune tolerance such as in transplantation and cancer –3. The iMany metabolic disorders are characterized as an imbalanced composition and function of intestinal microbiota with reduced microbial biodiversity and altered metabolic capacity, or gut dysbiosis , 12. In Faecalibacterium prausnitzii directly metabolizes tacrolimus into less potent metabolites in vitro . Samples were analyzed with an LSR Fortessa Cell Analyzer (BD Biosciences), and data were analyzed using FlowJo software version 10.6 (BD Biosciences).LNs were disaggregated and passed through 70-μm nylon mesh screens  to produce single-cell suspensions. Cell suspensions were treated with anti-CD16/32  to block Fc receptors, stained for 30 min at 4°C with antibodies against surface molecules  was calculated within demarcated high endothelial venules (HEV) and cortical ridge (CR) regions of the mLN and pLN as well as of whole intestinal images. The percent area was calculated by dividing the sum area of demarcated regions with marker fluorescence greater than a given threshold by the total area analyzed. Treatment groups were compared using quantification of MFI multiplied by percent area to express both the area and intensity of cell and stromal fiber markers. Qualitative heat maps were generated (GraphPad prism) to express changes in IHC marker expression level relative to control using 1 to represent “increased,” 0 to represent “unchanged,” and − 1 to represent “decreased.”Mesenteric and peripheral LN and segments of the intestine between the duodenum and jejunum were separately excised and immediately submerged in OCT compound  or fixed using paraformaldehyde. Cryosections (5 μm) were cut in triplicate using a Microm HM 550 cryostat (ThermoFisher Scientific) and fixed in cold 1:1 acetone:methanol for 5 min, washed in PBS, or left unfixed for fluorescent microscopy. Sections were rehydrated in PBS and blocked with 2.5% donkey serum and 2.5% goat serum in PBS. The sections were then stained at room temperature with primary antibodies (diluted 1:20 – 1:200 in PBS), blocked with 10% secondary antibody host serum, incubated with secondary antibodies (diluted 1:50 – 1:400 in PBS) for 30 min, fixed with 4% paraformaldehyde in PBS for 5 min, quenched with 1% glycerol in PBS for 5 min, and mounted with Prolong Gold Antifade Mountant with or without DAPI (Thermo Fisher Scientific). Images were acquired using a Nikon Accu-Scope EXC-500  and analyzed using Volocity software . The antibodies used are listed in Intestinal permeability was assessed as described previously . BrieflyDatasets were analyzed using GraphPad Prism 9.3.1  with statistical significance defined as P < 0.05. For comparisons of fluorescent markers (including laminin α4:α5 ratios), serum markers, and inflammation scores, Tukey’s multiple comparison tests of one-way ANOVA were used to test for significance.The jejunum and colon tissues of the mice were dissected according to their gastrointestinal anatomical features. Intraluminal stool contents were collected from dissected tissues and stored immediately in DNA/RNA Shields  at −80°C to stabilize and protect the integrity of nucleic acids and minimize the need for immediate processing or freezing of specimens. DNA extraction was described previously , 62. In Metagenomic sequence reads were removed using BMTagger v3.101  mapping Metabolome of intraluminal stool  and serum (circulating/systemic) were measured using capillary electrophoresis-mass spectrometry (CE/MS) to obtain a comprehensive quantitative survey of metabolites . ~10–30 mg of stool was weighed at the time of collection using a company-provided vial and archived at −80°C at the IGS until shipped to the HMT on dry ice. QC procedures included standards, sample blanks and internal controls that were evenly spaced among the samples analyzed. Compound identification was performed using a CE/MS library of > 1,600 annotated molecules.Selecting a proper data pretreatment method is essential in metabolomic data analyses to reduce the influence of measurement noise . The nor


Lyme disease (LD) is the most common vector-borne disease in the United States. The early localized disease presents with erythema migrans and nonspecific constitutional symptoms. A neurological manifestation of LD (neuroborreliosis) is only seen in 10-15% of LD cases, and it typically presents as cranial neuritis or painful radiculitis. We report a case of a 33-year-old male who presented with progressive ascending bilateral lower extremities weakness with paresthesia in hands and feet following an upper respiratory tract infection and an abdominal rash. Cerebrospinal fluid (CSF) analysis revealed albuminocytologic dissociation. An electrodiagnostic study showed prolonged distal motor latency, conduction block, and absent F-wave response. Magnetic resonance imaging of the lumbar spine revealed enhancement of the cauda equina nerve roots. After a lack of improvement with intravenous immunoglobulin for presumed Guillain-Barré syndrome (GBS), Lyme serologies were sent and showed positive Lyme antibodies in serum and CSF as well as positive western blot IgM followed by IgG seroconversion a week later. The patient was started on IV ceftriaxone and doxycycline for four weeks with significant improvement in his symptoms. This is a rare case of LD presenting as GBS. Lyme can have diverse neurologic manifestations and should be considered in the differential diagnosis of GBS in the appropriate settings. Borrelia burgdorferi and rarely by Borrelia mayonii, and it is transmitted by the bite of infected ticks of the genus Ixodes [Lyme disease (LD) is the most common vector-borne disease in the United States, with an annual report of 476,000 cases since 2010 [s Ixodes . LD can s Ixodes . NeuroboA previously healthy 33-year-old male with no chronic medical history presented with the progressive onset of bilateral hands and feet numbness associated with an ascending symmetric paraparesis  scale of 4/5 proximally and 3/5 distally). The patient reported that his symptoms started one week ago as a “tingling sensation” in his hands and feet with perioral numbness along with a concurrent fever, nonproductive cough, and a “blotchy” abdominal rash, which was not present upon admission. He denied any recent travel history or tick bite. He works as a 4th-grade teacher and frequently plays disc golf in wooded environments in his hometown in Ohio. The patient was afebrile upon presentation with no cough, chest pain, or shortness of breath. The physical exam also revealed bilateral facial palsy as well as hyporeflexia at his knees and ankles with downgoing plantar responses. The sensation to light touch was decreased below the elbows and up to his knees. Complete blood count (CBC) and basic metabolic panel (BMP) were within normal limits. Chest X-ray did not reveal any acute cardiopulmonary process. He underwent lumbar puncture, and CSF analysis revealed a white blood cell (WBC) count of 0 (range: 0-6 /uL), normal glucose of 57 mg/dL (range: 40-70 mg/dL), and mild protein elevation to 54 mg/dL (range: 15-45 mg/dL). MRI of the lumbar spine showed enhancement of the cauda equina nerve roots on post-contrast images  (0.4 g/kg/day). On hospital day three, his unremarkable baseline respiratory parameters deteriorated (negative inspiratory force (NIF) decreased from -40 cm H2O to -28 cm H2O and vital capacity (VC) reduced from 2300 mL to 1300 mL), along with difficulty managing oral secretions for which he was intubated and transferred to the neurocritical care unit for respiratory support and further management.By hospital day eight, the patient’s condition continued to worsen despite having completed IVIG treatment. The physical exam revealed severe quadriparesis in bilateral upper and lower extremities  with loss of sensation to light touch in all four extremities. His respiratory parameters continued to decline , and subsequently, a tracheostomy was performed. Given the lack of improvement with IVIG for presumed GBS, Lyme serologies were tested and showed positive Lyme antibodies in serum and CSF. Additionally, western blot IgM for LD tested positive with all three diagnostic bands  present. The patient was started on IV ceftriaxone and doxycycline for the concerns of neuroborreliosis. In the meantime, he developed dysconjugate gaze with bilateral ptosis. MRI brain with IV gadolinium showed increased multifocal abnormal cranial nerve (CN) enhancement involving CNs VII/VIII in the internal auditory canals and CN III bilaterally , in addition to positive western blot IgG, this time with five out of 10 diagnostic bands that are recommended by the Centers for Disease Control and Prevention (CDC) present , confirming the diagnosis of LD.Upon completion of a four-week course of antibiotics, the patient recovered sufficiently to be transferred to a long-term care facility. Two weeks later, the patient was weaned off ventilator support and discharged home. Eight months after the start of symptoms, the patient had recovered significantly. A follow-up exam in the neurology clinic revealed full upper extremities strength  with only diminished lower extremities dorsiflexion and plantar flexion  and mild paresthesia in his feet.Campylobacter jejuni is the most reported one [GBS is an immune-mediated polyradiculoneuropathy that classically presents with progressive (ascending) limb weakness and areflexia following an upper respiratory tract infection (URTI) or gastroenteritis. Several infections are associated with GBS, but rted one . In thisrted one . Our worrted one .Borrelia burgdorferi showed that only 26% of the patients recalled a tick bite, 46% noticed an erythema migrans and only 16% showed a skin rash (or residue of it) at the time of clinical evaluation [The lack of clinical improvement after completing five days course of IVIG along with the patient history of “blotchy” abdominal rash prior to presentation in addition to the reported outdoor activities in wooded environments questioned the validity of GBS and raised the concern about an alternative diagnosis. Therefore, Lyme serologies were tested and showed positive Lyme antibodies in serum and CSF. Our patient had positive IgM western blot within 30 days of symptom onset with all three diagnostic bands present. This was followed by IgG seroconversion a week later with five out of 10 diagnostic bands present. The combination of the above-mentioned results confirmed the diagnosis of LD. Despite that our patient denied recalling a tick bite associated with his rash, a prospective study of 187 patients with aluation . In addiThe pathophysiology of peripheral nerve injury in LNB is still unclear. Large studies have demonstrated multifocal lesions affecting both sensory and motor nerves acting as an axonal disease on NCS with relatively normal conduction velocities, only mild prolongation of late response latencies, and no evidence of conduction block . ControvOur patient had significant improvement two weeks after completion of the antibiotic course. Similar improvement of symmetric polyneuropathy following treatment for Lyme has been reported in rare instances. Tyagi et al. reported a 34-year-old woman with suspected GBS, which was refractory to a five-day course of IVIG and had significant improvement with subsequent antibiotic therapy once Lyme was diagnosed and treated . SimilarWe report a rare case of neuroborreliosis with clinical, radiographic, and neurodiagnostic findings mimicking GBS. Our high index of suspicion and comprehensive workup led to accurate diagnosis and appropriate management. LD can have diverse neurologic manifestations and should be considered in the differential diagnosis of GBS, especially when there is a history of outdoor activity. Early identification of this atypical pattern of presentation is the key to ensure quicker treatment and prevent disease progression.


The porcine mammary glands share morphological and physiological similarities with human ones, making primary porcine mammary cells (PMC) suitable for biomedical research and a potential cellular therapeutic for breast cancer xenogeneic cell immunotherapy. Primary cells isolated from tissues remain the physiological functions of origin tissues but their self-renewal ability is restricted and cells acquire senescence during in vitro expansion. To overcome these drawbacks, here we sought to establish an approach to efficiently increase PMC’s in vitro growth. We studied the effects of the hepatocyte growth factor (HGF) to maintain the expansion capacity of porcine mammary cells and identify the possible mechanisms.HGF could allow for the increase in vitro proliferation capacity of primary epithelial cells isolated from tissue samples. To effectively produce cells for biomedical research and xenogeneic cell therapy, we planned to study the effects of HGF and its potential mechanisms of action to stimulate cell growth for PMC expansion.After HGF treatment, the growth, cell cycle, senescence and the cell marker gene expression of PMCs were analyzed in standard 10% FBS and low serum 1% FBS containing medium.HGF significantly enhanced the cell proliferation by shifting the cell cycle population from G1 phase into S phase to increase cell division, reduced the senescent cells and reprogrammed gene expression profiles.We demonstrated that HGF could maintain the expansion capacity of PMCs by increasing cell growth and anti-senescence capability, suggesting its potential application in optimizing the long-term culture of primary cells. Adding a specific growth factor such as HGF in culture allows enhanced expansion of heterogeneous cell populations from normal porcine mammary glandular tissues in vitro. We believe that this cell culture approach will efficiently provide cells for studying mammary cell function and supply cells for therapeutic uses. Primary cell cultures obtain cells freshly and directly from dissected human or animal organ tissues and maintain them for growth in vitro . PrimaryThe mammary gland consists of parenchyma  and stroma . The human mammary gland composes a compound tubuloalveolar structure with luminal epithelial cells that are surrounded by myoepithelial cells to form an alveolus . AlveoliPrimary tissue cells like PMCs are sensitive to environmental signals by growth factors for growth and survival. Growth factors such as EGF, FGF and HGF enhance cell growth in vitro. However, it is not clearly defined whether any or all these growth factors are also important for PMC growth. To investigate the effect of these factors on the growth and expansion of PMCs, we tested the effect of these growth factors on PMC growth, cell cycle and senescence as well as the expression level of PMC progenitor and differentiation marker gene. We found that Hepatocyte Growth Factor (HGF), a pleiotropic growth factor that stimulates proliferation and migration of epithelial cells and endothelial cell through the binding to the proto-oncogenic c-Met receptor ,12, incrPMCs isolated from porcine mammary glands and expanded in vitro provide a suitable cellular model for studying human mammary gland biology, physiology and pathology, an alternative approach using animal cells to solve the scarcity of human tissues. PMCs also provide a safe animal source for xenogeneic cell therapy. Prolonged growth and further expansion of these cells could be achieved using HGF through regulating important cellular and molecular functions.2 pieces and then dissociated by digestion solution which contain 0.75 mg/ml collagenase D  in DMEM (Dulbecco’s modified Eagle medium) and 1 mg/ml type IV collagenase  in Hanks’ balanced salt solution , respectively. The dissociated cells and tissue fragments were cultured in DMEM/Ham’s F12 medium containing 10% FBS, 10 mM HEPES and antibiotics  and incubated at 37 °C in humidified atmosphere of 5% CO2. This initial passage of the primary cell culture was referred to as passage 0 (P0). Dissociated cells and outgrown cells of tissue explants were maintained in culture until they achieved 75–90% confluence. They were then either collected and cryopreserved or passaged. To separate epithelial cells from fibroblast cells, we used differential trypsinization, which removed the fibroblasts and enriched the strongly adherent epithelial cells (based on the cell morphology).The porcine mammary cells (PMC) were isolated from mammary glands, which were obtained from landrace (L), Yorkshire (Y) and Duroc (D) L-Y-D hybrid sows . Briefly, porcine mammary gland biopsy tissue was disinfected using povidone-iodine solution washed, and glandular structures were harvested and cut into 1–2 mm3 cell/well with different treatments. At the end of treatments, cell proliferation of PMCs was quantified using cell counting kit-8  following the manufacturer’s protocol. The absorbance was measured at 450 nm with a microplate reader . The average absorbance of the control wells (blank) was subtracted from that of the test wells with cells. All the data were then expressed as relative absorbance using the cells at day 0 or without treatments as a reference value. To determine the doubling time for each passage, cell divisions per passage were calculated as n = [logN−logN0]/log 2 where N is the absorbance of cells at harvest and N0 the absorbance of cells at seeding.PMCs were seeded in 96-well plates at 4 × 105 cells) were seeded in 6-well plates and incubated overnight. Cells were treated with HGF for 48 h. After 48 h, cells were trypsinized and fixed in 70% ethanol at 4 °C for 15 min. Centrifuge ethanol-suspended cells and remove ethanol. After two times washing with cold PBS, the cells were stained with 300 μL of staining solution  at 4 °C for 30 min and analyzed by the BD FACSCanto II flow cytometry . Data were then analyzed by Flowjo software.PMCs  activity was evaluated with a Senescence Detection Kit (K320-250) from Biovision  following the manufacturer’s instruction. Senescent cells were revealed as cells that were blue-stained by Bright-field microscopy. To determine the percentage of SA-βGal-positive cells, a total of 500 cells in 3 random views on each slide were counted to calculate the proportion of senescent cells in each group. Images were acquired at a magnification of 10X.Cells were plated at 5 × 10PMCs were seeded on 10 cm dish and incubated overnight and were then treated with HGF, for 3 days. After that, cells were lysis by cold RIPA buffer containing 1 × Protease inhibitor cocktail . The concentration of total protein levels was measured by a BCA protein assay kit . 40 μg of protein was separated by 10% sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), transferred onto to polyvinylidene difluoride (PVDF) membrane (Millipore) with a transfer apparatus . PVDF membranes were blocked in 5% non-fat dry milk dissolved in TBS buffer and then incubated with primary antibodies including mouse p16INK4a  and β-Actin (C4) antibody  overnight at 4 °C. The immunoblots were washed three times in TBS buffer for 10 min and then detected by the second antibody solution containing goat anti-mouse IgG-HRP (Santa Cruz) for p16INK4a, or goat anti-rabbit IgG-HRP (Santa Cruz) for β-Actin for 1 h in TBS buffer. The immunoblotted proteins were visualized using an enhanced Immobilon Western Chemiluminescent HRP Substrate Reagent  and detected by the Chemidoc XRS Chemiluminescent Gel Documentation Cabinet detection system (Bio-Rad).5 cell/well density and total RNAs were extracted from cells by using Trizol Reagent . Isolated RNAs were converted into cDNA by using DNA Synthesis Kit  via reverse transcription. PCR assays were performed using SYBR Green Dye  and a quantitative real-time PCR cycler. The PCR cycle conditions were set one cycle at 95 °C for 2 min, 40 cycles of 95 °C for 5 s, and 40 cycles at 60 °C for 30 s in order and run on a BioRad CFX96 Touch Real-Time PCR Detection System. Relative mRNA expression was calculated relative to GAPDH reference gene using comparative cycle threshold analysis by the 2 (−ΔΔCT) method [For qRT-PCR analysis, PMCs were seeded in 6-well plates at 1–2x10) method . Primers) method .All the data are presented as mean ± standard deviation (SD). Statistical analyses were carried out using GraphPad Prism and differences between two populations (vehicle group vs HGF group) were calculated by Student’s t-test. P values < 0.05 were considered statistically significant.We successfully isolated PMCs from adult porcine mammary glands using mechanic and enzymatic processes and cultured the dissociated and explant outgrowth cells in DMEM/F12 medium for at least 12 passages. Cells displayed a monolayer of heterogeneous morphologies with most cobblestone, some oval, and luminal epithelial like shapes . Based oTo identify the growth factors that could enhance the growth potential of PMCs, we selected several factors which regulate the proliferation, progenitor state, or differentiation of primary tissue cells such as HGF. We investigated the effect of HGF and its effective concentrations to promote the expansion of PMCs by culturing PMCs in medium supplemented with HGF with different concentrations for 5 days. We found that HGF promoted the growth of PMCs reaching a maximum effect at 50 ng/ml . Both thTo investigate how HGF controls PMC proliferation, cell cycle events were measured. We investigated the cell cycle distribution of PMCs treated with HGF in 10% and 1% FBS medium . The celAfter a certain number of cell divisions, primary cells will stop dividing and enter into senesce, which is a built-in replicative limit, called the Hayflick limit . The HayTo further understand the effect of HGF on PMC cells, the RNA expression levels of the marker genes were measured. We used RT-qPCR to monitor progenitor or differentiation-related genes. Protein C receptor (PROCR) gene, a novel Wnt target in the mammary gland that is involved in mammary epithelium cell regenerative and multiple differentiation capacities into all lineages of the mammary epithelium , was higWe identified HGF as an active supplement in the culture of PMCs. HGF is able to increase cell growth  possiblyHGF could bind to sulfated glycosaminoglycans heparan sulfate and dermatan sulfate allowing HGF to form a complex with c-Met that is able to transduce intracellular signals leading to cell division and cell migration . In thisPMCs derived directly from porcine mammary glands provide a mammary tissue specific cell model, but can only be maintained in vitro for a limited period of time with a finite short life span in conventional tissue culture conditions and thus restricted expansion capacity. Cell expansions are essential to obtain primary tissue cells because the primary cultures could be reestablished as secondary cultures that are further passaged, but eventually exhibited senescence, restricting the expansion of primary cells. The mortality stage l (MI) mechanism is activated near the end of the normal proliferative lifespan of cells and this is the process commonly viewed as in vitro senescence . The limIt is necessary to maintain the progenitor population of PMCs during long-term expansion to sufficiently produce PMCs in quantity for research and therapeutic purposes. We showed that HGF treatment could turn on the progenitor related PROCR gene, but inhibit differentiation marker gene CSN2  which suIn this study, the growth of PMC could be enhanced by HGF in 10% FBS and to a higher degree in 1% FBS medium. We identified HGF as a key factor to expand PMCs by increasing cell cycle, suppressing cell senescence in long-term culture of primary cells as well as maintaining the cells in progenitor state. Identifying the defined factors to expand primary cells is critical in order to get enough cells for both research and clinical applications. Our results indicate that HGF may support the consistent and efficient growth and expansion of porcine primary mammary cell. Due to the potential use of primary porcine mammary cells in biomedical research as well as cell-based therapy and regenerative medicine, further research is warranted to determine the factors needed to expand the cells.


Mycobacterium tuberculosis (Mtb) as defined by persistently negative tuberculin skin tests (TST) and interferon gamma release assays (IGRA). This group has been identified and defined as HIV+ persistently TB, tuberculin and IGRA negative (HITTIN). To investigate potential innate mechanisms unique to individuals with the HITTIN phenotype we compared their neutrophil Mtb infection response to that of PLWH, with no TB history, but who test persistently IGRA positive, and tuberculin positive (HIT). Neutrophil samples from 17 HITTIN (PMNHITTIN) and 11 HIT (PMNHIT) were isolated and infected with Mtb H37Rv for 1h and 6h. RNA was extracted and used for RNAseq analysis. Since there was no significant differential transcriptional response at 1h between infected PMNHITTIN and PMNHIT, we focused on the 6h timepoint. When compared to uninfected PMN, PMNHITTIN displayed 3106 significantly upregulated and 3548 significantly downregulated differentially expressed genes (DEGs)  whereas PMNHIT demonstrated 3816 significantly upregulated and 3794 significantly downregulated DEGs following 6h Mtb infection. Contrasting the log2FC 6h infection response to Mtb from PMNHITTIN against PMNHIT, 2285 genes showed significant differential response between the two groups. Overall PMNHITTIN had a lower fold change response to Mtb infection compared to PMNHIT. According to pathway enrichment, Apoptosis and NETosis were differentially regulated between HITTIN and HIT PMN responses after 6h Mtb infection. To corroborate the blunted NETosis transcriptional response measured among HITTIN, fluorescence microscopy revealed relatively lower neutrophil extracellular trap formation and cell loss in PMNHITTIN compared to PMNHIT, showing that PMNHITTIN have a distinct response to Mtb.Persons living with HIV (PLWH) have an increased risk for tuberculosis (TB). After prolonged and repeated exposure, some PLWH never develop TB and show no evidence of immune sensitization to  Mycobacterium tuberculosis (Mtb), the causative organism of TB, once Mtb is inhaled. Our study used two populations: i) persons who are living with HIV (PLWH), have no history of TB and test persistently negative for Mtb T cell sensitization (HITTIN); and ii) PLWH who have a positive Mtb-specific T cell response with no previous TB (HIT). Specifically, we compared neutrophil response to Mtb and compared HITTIN to HIT. Compared to neutrophils from HIT persons, HITTIN neutrophils (PMNHITTIN) show significant gene expression differences in response to Mtb infection. Unexpectedly, our results show PMNHITTIN have a global lower response to Mtb infection with fluorescent microscopy revealing lower neutrophil extracellular trap (NET) formation in PMNHITTIN compared to PMNHIT after 6h infection with Mtb. NETs are weblike structures and are formed from decondensed DNA during a unique form of cell death named NETosis. This data highlights PMNHITTIN as important immune cells in response to Mtb in HITTIN.Neutrophils can contribute to the severity of tuberculosis (TB). More recently TB protective mechanisms of neutrophils have also been highlighted. We examined the gene expression of neutrophils, one of the first immune cells to make contact with  Mycobacterium tuberculosis (Mtb) protein antigens and are used as a surrogate for prior Mtb infection. Despite these persons having a history of previously low CD4+ T-cell counts, prior to antiretroviral therapy (ART), they display no canonical evidence of prior Mtb infection or history of disease . NADPH oxidase Nox2 (encoded by CYBB) and other cellular NADPH oxidases is involved with ROS production and NET formation , 0.8% Sodium bicarbonate  and 0.4% Ethylenediaminetetraacetic acid ).Neutrophils were isolated by Ficoll gradient separation. Whole blood diluted 1:1 with 1x Phosphate buffered saline  was layered over the density gradient separation medium . Cells were centrifuged for 25 minutes at 400 x g. After this, cells were washed twice with 4°C PBS and centrifuged each time at 400 x g for 10 minutes at 4°C. Peripheral blood mononuclear cells were removed first and then the remaining plasma and Ficoll-Paque layer. A red blood cell (RBC) lysis buffer (component concentrations) was added in a ratio of 1:10 or topped up to 50ml, if a 50 ml centrifuge tube was used, to the remaining bottom layer and incubated for 10 minutes at 4°C. RBC lysis buffer , were seeded evenly over each row of 3 wells in a 6-well plate cell culture plate  at 0.33 x 107 cells per well for the RNA sequencing experiment and 2 x 105 cells per well in a 96-well  for microscopy. For each participant two 6-well plates  were seeded. Cells were incubated for 1h-2h at 37°C and 5% CO2. An aliquot of remaining neutrophils was fixed with 4% Paraformaldehyde  and then stored overnight at -80°C before transferred to and stored in liquid nitrogen.After RBC lysis, samples were centrifuged at 400 x g for 10 minutes at 4°C and then washed twice with PBS (4°C) and centrifuged at 400 x g for 10 minutes at 4°C. After the cell count, 1 x 106 cells per participant were resuspended in surface staining buffer comprised of DPBS + 3% Foetal Bovine Serum . Fluorescently conjugated antibodies for cell surface staining . 1.5 x 10staining  were preMtb single cells stocks for infection were prepared as previously described  and 2° antibody cocktail [1:1000 α-mouse-Cy3  and 10μg/ml Hoechst 33342 ] –74. PrioImage tile scans were acquired with the Zeiss AxioObserver Z1 microscope, equipped with a Colibri 7 light source for excitation of Hoechst 33342  with LED-module 385nm, and Cy3 with LED-module 511nm. A quadruple band pass filter and triple band pass filter were used respectively for detection of Hoechst (wavelength range 412-438nm) and Cy3 (wavelength range 546–564 nm). Images were acquired with a LD A-Plan 40x/0.55 objective as a 6 x 8 tile scan to acquire a total area of 1.21mmx1.21mm .Tiles were stitched together into single images using Zeiss ZenPro software (version 2.6), which were imported into FIJI/ImageJ (version 1.53t). Image tiles were split into separate channels, after which background subtraction (ranging from 50–100 pixels) and Otsu based thresholding was conducted on a per image basis to generate a binarized map of each image. Binary images were further processed by using the binary closing function in FIJI, as well as a top hat filter of 1–2 pixels to remove small non-specific pixels. For the nuclear quantification, an additional watershed function was applied to separate borders more accurately. Thereafter, morphometric data were obtained by specifying the area and circularity ranges of particles to be analysed through the Analyze Particles function in FIJI to determine the total area covered.7 cells for each) were lysed with TRIzol  after 1h and 6h after infection, and stored at -80°C. The miRNeasy kit  was used for total RNA extraction. One sample per participant and condition was used. RNA integrity (RIN) was assessed with the Agilent 2100 Bioanalyzer . Samples with RIN >7 were selected for library preparation using TruSeq RNA Library Preparation Kit v2, Set A . Samples were sequenced in two batches  and MultiQC ,76. The Batch 1 and 2 were combined after read counts were generated. For read count generation the same method was applied to both batches. After initial raw sequence quality check by FastQC, data was filtered and trimmed using HTStream ,78. The The genome was indexed using GRCh38.p13 v34 (ENSEMBLE v100) and reads were aligned to the genome with STAR (v2.5.3a) in a bam format –81. MoreRaw counts were transformed to counts per million (CPM) and filtered using “filterByExpr” in the edgeR package . Briefly2 CPM and sample specific weights were incorporated with abundance dependent weights using limma’s (v3.46.0) function “voomWithQualityWeights”  and infected [INF]) and as depicted in the legend. Separation of the groups by time can be seen in dimension 1, by infection in dimension 2 and the phenotype in dimension 3. Additional separation is seen in dimension 4 and 5 due to sex and possibly smoking see  Figs.(PDF)Click here for additional data file.S9 FigThe top 5 principal components are represented on the x-axis and the variance explained by each component on the y-axis. Principal component (PC) 1 contributes to most of the variance seen and represents time. PC2 represent infection effect and PC3 the phenotype groups.(PDF)Click here for additional data file.S10 FigThe multidimensional scaling (MDS) plots the Euclidian distances between samples with the x and y axis representing the sample distances between samples of read counts normalized by depth but not covariates. Each row of plots in represent dimension 1 to 5 respectively (represented by the x-axis) and shown with the combination of the other dimensions on the y-axis. Samples are colored for sex  as depicted in the legend. Separation is seen in dimension 4 and 5.(PDF)Click here for additional data file.S11 FigThe multidimensional scaling (MDS) plots the Euclidian distances between samples with the x and y axis representing the sample distances between samples of read counts normalized by depth but not covariates. Each row of plots in represent dimension 1 to 5 respectively (represented by the x-axis) and shown with the combination of the other dimensions on the y-axis. Samples are colored for participants classified as smokers or not as depicted in the legend. Each participant is represented by 4 dots . There are only two smokers making it difficult to comment on separation due to smoking.(PDF)Click here for additional data file.S12 FigThe multidimensional scaling (MDS) plots the Euclidian distances between samples with the x and y axis representing the sample distances between samples of read counts normalized by depth but not covariates. Each row of plots in represent dimension 1 to 5 respectively (represented by the x-axis) and shown with the combination of the other dimensions on the y-axis. Samples are colored for participants classified as either having used INH prophylaxis previously/currently or not, as depicted in the legend. There is no clear separation based on INH prophylaxis use.(PDF)Click here for additional data file.S13 FigThe multidimensional scaling (MDS) plots the Euclidian distances between samples with the x and y axis representing the sample distances between samples of read counts normalized by depth but not covariates. Each row of plots in represent dimension 1 to 5 respectively (represented by the x-axis) and shown with the combination of the other dimensions on the y-axis. Samples are colored for the numbers of months participants previously used INH  or participants who are currently using INH, as depicted in the legend. There is no clear separation based on duration of INH prophylaxis use.(PDF)Click here for additional data file.S14 FigThe multidimensional scaling (MDS) plots the Euclidian distances between samples with the x and y axis representing the sample distances between samples of read counts normalized by depth but not covariates. Each row of plots in represent dimension 1 to 5 respectively (represented by the x-axis) and shown with the combination of the other dimensions on the y-axis. Samples are colored for participants classified as either having a chronic disease or not, as depicted in the legend. There is no clear separation based on participants with chronic disease.(PDF)Click here for additional data file.S15 FigThe multidimensional scaling (MDS) plots the Euclidian distances between samples with the x and y axis representing the sample distances between samples of read counts normalized by depth but not covariates. Each row of plots in represent dimension 1 to 5 respectively (represented by the x-axis) and shown with the combination of the other dimensions on the y-axis. Samples are colored for participants classified as either using alcohol or not, as depicted in the legend. There is no clear separation based on participant alcohol use.(PDF)Click here for additional data file.S16 FigThe multidimensional scaling (MDS) plots the Euclidian distances between samples with the x and y axis representing the sample distances between samples of read counts normalized by depth but not covariates. Each row of plots in represent dimension 1 to 5 respectively (represented by the x-axis) and shown with the combination of the other dimensions on the y-axis. Samples are colored for participants classified according to their BMI, as depicted in the legend. NA represents samples with missing values and is shown in grey. There is no clear separation based on participant BMI.(PDF)Click here for additional data file.S17 FigThe multidimensional scaling (MDS) plots the Euclidian distances between samples with the x and y axis representing the sample distances between samples of read counts normalized by depth but not covariates. Each row of plots in represent dimension 1 to 5 respectively (represented by the x-axis) and shown with the combination of the other dimensions on the y-axis. Samples are colored for participants classified by age, as depicted in the legend. There is no clear separation based on participant age, although there is an older outlier seen in dimensions 3.(PDF)Click here for additional data file. 13 Jun 2023Dear Dr Kroon,Thank you very much for submitting your Research Article entitled 'Altered neutrophil extracellular traps in response to Mycobacterium tuberculosis in persons living with HIV with no previous TB and negative TST and IGRA' to PLOS Genetics.The manuscript was fully evaluated at the editorial level and by independent peer reviewers. The reviewers appreciated the attention to an important problem, but raised some substantial concerns about the current manuscript. Based on the reviews, we will not be able to accept this version of the manuscript, but we would be willing to review a much-revised version. We cannot, of course, promise publication at that time.Should you decide to revise the manuscript for further consideration here, your revisions should address the specific points made by each reviewer. We will also require a detailed list of your responses to the review comments and a description of the changes you have made in the manuscript.plosgenetics@plos.org.If you decide to revise the manuscript for further consideration at PLOS Genetics, please aim to resubmit within the next 60 days, unless it will take extra time to address the concerns of the reviewers, in which case we would appreciate an expected resubmission date by email to Submission Checklist.If present, accompanying reviewer attachments are included with this email; please notify the journal office if any appear to be missing. 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You will be contacted if needed following the screening process.PLOS has incorporated To resubmit, use the link below and 'Revise Submission' in the 'Submissions Needing Revision' folder.We are sorry that we cannot be more positive about your manuscript at this stage. Please do not hesitate to contact us if you have any concerns or questions.Yours sincerely,Cathy SteinGuest EditorPLOS GeneticsScott WilliamsSection EditorPLOS GeneticsThe reviewers generally had a positive assessment of this work. However, there are many points that require clarification.Reviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: In their manuscript "Altered neutrophil extracellular traps in response to Mycobacterium tuberculosis in persons living with HIV with no previous TB and negative TST and IGRA", Kroon and colleagues explore neutrophil gene programs that distinguish a clinical phenotype of great interest. They compare well-defined cohorts of PLWH in South Africa who have presumed exposure to M. tuberculosis, which is based both on residence in a high endemic setting and Mtb-specific antibody responses, in order to explore potential mechanisms by which some immune-reconstituted PLWH lack canonical Mtb sensitization (TST/IGRA reactivity) with the hope to identify non-canonical mechanisms that protect them from TB progression. The manuscript is well crafted and written, and while it builds on a growing literature that explores IFNg independent mechanisms of TB protection among similarly defined clinical phenotypes (TST/IGRA based), the authors add novelty by focusing on PLWH where protective mechanisms may be distinct. Another strength is the inclusion of immunofluorescent microscopy evidence of NET formation to validate transcriptional findings.While overall the composition is clear, there are a few areas where the narrative that builds from global transcriptional profiling (e.g. DEG identification and pathway enrichments) to experimental NET data could be made more clear.Major comments:Title:- Title is confusing, perhaps because TST and IGRA syntax is awkward. Consider an alternative such as "Neutrophil extracellular trap formation and gene programs distinguish TST/IGRA sensitization outcomes among M. tuberculosis exposed persons living with HIV."Figures 2 and 3 and corresponding section (lines 189-210):The various analyses lead to some confusion assuming the overall conclusion of this section appears in the section heading. Examples and suggestions:1) Figure 2 - Can a statistical statement be made whether the 6hour distributions (HITTIN versus HIT) are different?2) The importance of the log2FC correlations  is not evident and leads to confusion based on the section heading.- the statement (line 199) "differential expression across phenotypes was correlated with log2FC" needs to be better defined. To what the 'differential expression' refer since log2FC also describes differential expression (media - infection).- Am I correct in stating the null hypothesis in this sense has not been rejected ? If that is true, I would consider moving Fig3 to supplemental and make a simple statement in Results such as 'despite overall lower log2FC among HITTIN, there was a strong correlation of log2FC values for each gene between HITTIN and HIT suggesting that Mtb responses globally are conserved across phenotypes.'3) Suggest removing 1h data in main results section to further streamline main conclusion and avoid unnecessary comparisons. It seems authors have concluded 1h is too early given insufficient transcriptional changes. The statement justifying a focus on 6h time point could be make earlier with reference to supplemental info for 1h timepoint data).HITTIN vs HIT interaction DEG model:(lines 205 - 210) - The model used when comparing HITTIN against HIT needs [a brief] reference in main results section. Presumably these 2285 DEGs reflect the interaction between (uninfected - Mtb) *(HIT - HITTIN), but is restricted to the 6h timepoint? As written, it suggests a simple contrast model was used that is restricted to Mtb-infected samples (6h) only. I also note in the methods section that infection time (1h - 6h) was also included in the DEG model that may further lend confusion to interpretation of this main results section (and 2285 DEGs).Directionality of NET term enrichments (and NADPH oxidase DEGs).(line 229) Reference to 'terms that directly relate to a possible increased microbicidal activity of PMN-HITTIN' leads to a confusing directionality based on subsequent sections that highlight genes that actually have reduced expression in HITTIN.- (line 230) should be 'Fig 4B'.- NADPH oxidase genes  had decreased expression among HITTIN as described in Results and negative log2FC in Table 3. The positive enrichment among HITTIN of the NET formation pathway (higher NETs among HITTIN?) lends well to the later experimental data but seems contradictory to the gene-level directionality that is highlighted.- Reordering these sections by including the NET microscopy data immediately after reporting the positive HITTIN enrichment for the NET formation pathway in 4B may be easier to follow. Once the conclusion that NETs are lower in HITTIN is made, then further exploration at the gene-level can be made (Table 3 and results section 'DEGs in HITTIN vs HIT...').Limitations- Considering HITTIN have lower magnitude of transcriptional changes following Mtb infection overall, a contribution from non-PMN populations in the experiment should be considered. Contaminating T cells could plausibly contribute to IFNg-driven PMN transcriptional differences that are detected according to the pre-defined clinical phenotype.- It would be appropriate to mention this limitation, and that good PMN purity  and the 6h timepoint that is short for paracrine effects argue against a significant impact of contaminating cell types.- Considering the sensitivity of RNAseq it would be further reassuring to confirm there are not other IFNg pathway-related enrichments between HIT vs. HITTIN.- Note that IFNg even after short stimulation times can impact PMN NADPH oxidase expression (and NADPH production) in vivo:https://doi.org/10.1371/journal.pone.0263370- https://doi.org/10.1182/bloodadvances.2021005776- Minor comments:- Data access: Submission of data to the European Genome-phenome Archive (EGA) is currently being reviewed. Please confirm submission is processed/finalized.- ; Consider "some PLWH never develop TB and show no evidence of immune sensitization to Mycobacterium tuberculosis (Mtb) as defined by persistently negative tuberculin skin tests (TST) and interferon gamma release assays (IGRA)."- Consider including FDR threshold in Abstract to define significant- (lines 67 - 72) - differentially expressed is not defined initially and leads to confusion since the primary comparison as defined above is HITTIN versus HIT. Suggest better delineating with "When compared to uninfected PMNs, PMNhittin displayed 151 unregulated and 40 down regulated differentially expressed genes (DEGs) (FDR XX) whereas PMNhit demonstrated 98 upregulated and 11 downregulated DEGs following 1h of Mtb infection.- (line 72) - As above, consider adding "...3794 significantly downregulated DEGs when comparing Mtb-infected and uninfected PMNs.- (lines 111 - 120) Is there a reason why the PMN abbreviation is not assigned after first neutrophil use, or at least why this sentence is chosen for PMN abbreviation when neutrophil is spelled out later as well?- (line 155-158) consider change to "...11 HIT individuals, all of whom were PLWH and on ART, were used in the final analysis (Table 1). These individuals were part of stringently defined cohorts living in a high TB burden community who despite low CD4+ counts before ART initiation never developed TB."- Figure 1 - Legend suggests vertical line reflects log2FC of -/+ 0.02 whereas results section  suggests this should be -/+ 0.2.- Figure 4 - legend (line 1057) should have 'HIT' not 'HT'.- (line 230) reference should be Fig 4B.- (line 244-245) change to "NADPH oxidation by Nox2 (encoded by CYBB) and other cellular NADPH oxidases is involved with ROS production and NET formation (29-31)."- (line 277) should be "induced at 1h and 6h post infection".- (lines 291 - 292) Incomplete sentence.- (line 322) change to "Mtb-induced ROS triggered necrosis in neutrophils..."- (line 349) change to "TLR2/4 signaling could also mediate NET formation independent of ROS" or "ROS-independent mechanisms could also mediate NET formation downstream of TLR2/4."- (line 371-372) suggest change to "....maintained by PMN-HITTIN, which demonstrate lower NET formation in response to Mtb infection despite a positive enrichment of NET-related genes as compared to PMN-HIT."Reviewer #2: In this manuscript, Kroon and colleagues present the results of a RNAseq study on neutrophils in response to Mycobacterium tuberculosis (Mtb) challenge in persons living with HIV who are at high risk of TB. They compared the transcriptome profile of neutrophils after Mtb infection in 17 HIV+ persistently TB, tuberculin and IGRA negative (HITTIN) participants living in a community with high TB burden and 11 individuals living with HIV from the same community with no TB history, but who test persistently IGRA positive, and tuberculin positive (HIT). After 6h of infection, neutrophils of HITTIN participants showed an overall transcriptional impairment as compared to HIT participants, consistent with the lower number of differentially expressed genes (DEGs) in HITTIN vs HIT sujects (3106 vs 3816 up-regulated genes and 3548 vs 3794 down-regulated genes). When comparing the response to Mtb between HITTIN and HIT individuals, the authors identified 2285 significant genes. Genes with a significant positive fold change  were enriched in « Apoptosis », « Neutrophil extracellular trap formation », and “NADPH regeneration” pathways. Interestingly, lower neutrophil extracellular trap formation was observed by fluorescence microscopy in HITTIN compared to HIT participants.This manuscript tackles an important subject in the field of tuberculosis and suggest that NETosis could play a role in the early control of Mtb infection. I do, however, have some concerns regarding the robustness and interpretation of the findings.1) My main concern pertains to the overall transcriptional impairment after 6h of Mtb infection observed in neutrophils of HITTIN participants compared to HIT participants. I am wondering whether it could be attributed to systematic differences not accounted for between the two groups that influence the transcriptional responsiveness of neutrophils to Mtb. Notably, previous studies by some of the authors have demonstrated that antiretroviral therapy (ART) significantly affects the transcriptional responsiveness of alveolar macrophages to Mtb . Hence, I am curious if the duration of ART treatment in the participants could partially account for the observed overall impairment in neutrophils. It is essential to investigate, account for, and discuss this possibility.2) Related to the previous point, I am also concerned about how this transcriptional impairment may have impacted the results of the differential gene expression (DEG) analysis between HITTIN and HIT individuals. The ability to detect differences between the two groups is likely higher for genes that exhibit a robust response in HIT participants following Mtb infection. Consequently, I am wondering whether the enriched pathways could reflect the general response of neutrophils to Mtb rather than a differential expression pattern between HITTIN and HIT groups. It would be helpful to show the results of the pathway enrichment analysis in response to Mtb performed separately for HITTIN and HIT. Are the terms « Apoptosis », « Neutrophil extracellular trap formation », and “NADPH regeneration” significantly enriched in differentially expressed genes ? How do they rank in terms of significance in the two groups? This should be discussed.3) I am wondering if normalizing the expression profile of the HITTIN subject after 6 hours of Mtb infection to render it more comparable to HIT participants could make sense and how it could impact on the results of the DEG analysis between HITTIN and HIT groups?Reviewer #3: Very well written paper. This explores an important and relevant topic (understanding the immune response to TB infection in HITTIN and more broadly PLWH) and the authors explain and lay out the justification for this research appropriately. The introduction appropriately lays out the relevant background information on immune responses to TB, and the role of neutrophils/PMN's. Methodologically, the HIT group is an appropriate comparator for this study and the selection of subjects was adequately explored and justifiable, including an exploration of risk factors which would potentially serve as confounders. Differential gene expression in neutrophils/PMN's is an appropriate outcome for this question and the analysis was performed according to accepted standards. The authors further added to their understanding of the neutrophil response by examining the functional role of the DEG's they identified (showing enrichment for extracellular traps). Their microscopy validation was a nice way to wrap this up.Overall, this answers an important research question and the study is appropriately performed and the paper is well written. The results are impactful and significant. The discussion was also well-written and helps contextualize the importance of these results.**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********what does this mean?). 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Inform journal staff as soon as possible if you are preparing a press release for your article and need a publication date.Thank you again for supporting open-access publishing; we are looking forward to publishing your work in PLOS Genetics!Yours sincerely,Cathy SteinGuest EditorPLOS GeneticsScott WilliamsSection EditorPLOS Geneticswww.plosgenetics.orgTwitter: @PLOSGenetics----------------------------------------------------Comments from the reviewers (if applicable):You may want consider making the changes suggested by the Reviewer 1 regarding wording, as these will strengthen the paper.Reviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: All previous recommendations have been appropriately addressed. Several minor notes/considerations are as follows should authors/editor choose to modify.Abstract- penultimate sentence -- Suggest to avoid 'enrichment of genes in PMN-HITTIN' that may erroneously be understood by the reader as a pathway that is transcriptionally unregulated. An alternative could be "According to pathway enrichment, Aptotosis and NETosis were differentially regulated between HITTIN and HIT PMN responses after 6h Mtb infection. To corroborate the blunted NETosis transcriptional response measured among HITTIN, fluorescence microscopy revealed relatively lower neutrophil extracellular trap formation and cell loss in PMN-HITTIN as compared to PMN-HIT.'- Would suggest a broad conclusion final sentence after (maybe with an impact or future study statement).- A major (?) conclusion that global transcriptional responses are lower in HITTIN is missing from abstract (yet appears in author summary) whereas very specific data from 1h time point is included. Considering 1h information was moved to supplemental, consider revisiting this choice for abstract content.Author summary - should be "..we examined neutrophil responses to Mtb and compared HITTIN to HIT" or otherwise clarify since compare refers to two different 'to'.Minor issues(4th line abstract) - delete extra period- Sentence "We used fluorescent microscopy to evaluate the biological outcome..." seems to better fit under the heading that follows this paragraph. It would benefit from a transition to link findings from previous section, maybe just by reordering "To directly evaluate the biological outcome in the total amount of NETs observed between HITTIN vs. HIT, as is suggested by our transcriptional enrichments, we used fluorescent microscopy to quantitate NET formation." Also, the reference to Table 3 in this original sentence seems out of place .- Limitations - should be "we employed subject-specific fold changes."Reviewer #2: I would like to thank the authors for their time and effort to answer my comments. I have no additional concern.**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #1: YesReviewer #2: Yes**********what does this mean?). 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PLOS Genetics may also choose to issue a press release for your article. If there's anything the journal should know or you'd like more information, please get in touch via  18 Aug 2023PGENETICS-D-23-00472R1 Mycobacterium tuberculosis exposed persons living with HIV Neutrophil extracellular trap formation and gene programs distinguish TST/IGRA sensitization outcomes among Dear Dr Kroon, Mycobacterium tuberculosis exposed persons living with HIV" has been formally accepted for publication in PLOS Genetics! Your manuscript is now with our production department and you will be notified of the publication date in due course.We are pleased to inform you that your manuscript entitled "Neutrophil extracellular trap formation and gene programs distinguish TST/IGRA sensitization outcomes among The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. 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