Expression of either WH1(A31V)-mCh or WH1(ΔN37)-mCh was performed from low copy-number plasmids under the control of the Ptac promoter (described in Gasset-Rosa et al., 2014). A construct just carrying the mCherry protein (Molina-García and Giraldo, 2014) was used as a control. As bacterial host, the reduced genome E. coli K-12 strain MDS42 recA (Pósfai et al., 2006) was used in all experiments because it provides a simplified ‘chassis’ carrying the essential metabolic and regulatory pathways. Bacterial cells were transformed with the plasmids and grown at 37°C in 200 mL of rich LB medium (supplied with 2 mg⋅mL^-1 thymine and 100 μg⋅mL^-1 ampicillin) with good aeration in 1 L Erlenmeyer flasks. Induction was achieved by adding IPTG to 0.5 mM when cultures reached OD_{600 nm} = 0.2. Cells were harvested at various post-induction intervals, washed and, for the transcriptomic and interactomic analyses, immediately frozen in liquid nitrogen and then transferred to -70°C for storage. Cells (4⋅10⁸-3⋅10⁹, depending on the assay) were collected from at least three independent culture replicas.

Bacterial cells were observed with a Nikon Eclipse 90i microscope, equipped with a CFI PLAN APO VC 100x (NA 1.40) oil immersion objective and a Hamamatsu ORCA-R² CCD camera. For mCherry fluorescence, a 543/22 nm excitation and 593/40 nm emission filter and 200 ms exposures were used. Differential interference contrast (DIC) shots (100 ms) were also captured. Images were analyzed using the NIS-Elements AR software (Nikon). Bacterial culture aliquots were fixed in formaldehyde and mounted on poly-L-lysine coated slides, as described in Fernández-Tresguerres et al. (2010).

In a first approach, E. coli bulk cultures, expressing or not the RepA-WH1 prionoid, were grown as indicated above. Upon IPTG induction, every 30 min 4⋅10⁸ bacterial cells were harvested and lysed. The levels of ATP were determined in vitro using the ATP Bioluminiscence assay HSII (Roche), which is based on the requirement of ATP by firefly luciferase to process luciferin and emit light at 562 nm. Samples were dispensed in 96 wells black-walled microtiter plates and read-outs acquired in a TD-20/20 Turner Designs luminometer. Plots were corrected to the dry weight of cells.

In a second approach, bioluminiscence was monitored in real time in microscale cultures. In this assay, bacteria carried the vector for the expression of WH1(A31V)-mCh (Gasset-Rosa et al., 2014) plus mini-CTX-lux (Becher and Schweizer, 2000), a plasmid constitutively expressing the Photorhabdus luminescens luxCDABE operon from the kanamycin promoter. Cultures in LB (no antibiotics added) at OD_{600 nm} = 0.05 were fractioned in 200 μL aliquots and displayed in 96 well, flat bottom and black-walled, Grenier Chimney plates. When required, IPTG was supplied to 0.5 mM at the beginning of the experiment and each plate was then incubated in a Tecan infinite M200 PRO plate reader for 24 h at 37°C. At 30 min intervals, plate was agitated for 5 s (2 mm amplitude) and the following variables were sequentially measured: absorption (at 600 nm, 9 nm bandwidth), luminiscence (1 s integration time) and fluorescence (546 nm excitation, 9 nm bandwidth; 600 nm emission, 20 nm bandwidth; 25 flashes for 20 μs). Data were normalized to the OD_{600 nm} values. For each experiment, three replicas were set up.

Bacterial cultures were grown as specified above and iron concentration in the cell pellets was determined based in the ability of ferrozine to form a complex with Fe²⁺ that absorbs light at 562 nm (Honn et al., 2012). Volumes proportional to the cell densities in the cultures (1.0 OD_{600 nm}≈ 8⋅10⁸ bacteria) were taken at time intervals and then cells were harvested, washed and resuspended in PBS buffer. Bacteria were lysed with 100 μL NaOH and then neutralized with 100 μL of 10 mM HCl. Cell lysates were incubated with 100 μL of protein uncoupling solution (0.7 M HCl, 2.25% KMnO₄) for 2 h at 60°C. Then samples were incubated for 30 min with 100 μL of 6.5 mM ferrozine, 6.5 mM neocuproine, 2.5 M ammonium acetate, 1 M ascorbic acid, and the mixture was centrifuged for 30 s at 13,000 rpm. A_{562 nm} was measured for all supernatants in a Varioskan Flash (Thermo scientific) plate reader. The values of absorption obtained were normalized to the dry cell weight. The whole set of samples was processed at the same time for each replica of the assay to achieve reproducibility.

Cells were grown aerobically, as described above, or anaerobically in LB medium supplemented with 10 mM nitrate as terminal electron acceptor and 5 mM cysteine as reducing agent. Bottles with 20 ml of LB medium, as well as the nitrate and cysteine stock solutions (100x), were flushed with N₂, sealed with rubber stoppers and aluminum foil and then autoclaved. Then bottles were introduced in an anaerobic chamber (Forma anaerobic system 1029 S/N, Thermo Scientific) in which the air was continuously interchanged with a mixture of N₂ and biogas (10% H₂, 5% CO₂ and 85% N₂). The nitrate and cysteine supplements and the bacterial inocula were injected into the bottles through the stopper and cultures were incubated at 37°C under low shaking conditions (150 rpm). Bacterial growth was monitored as OD_{600 nm}. Serial dilutions of the cultures at initial-log phase were plated on LB-agar, which had been supplemented with nitrate and cysteine and left to stand at the anaerobic chamber for at least 24 h before usage. The rest of bacteria were induced with 0.5 mM IPTG and further grown until reaching mid-log and then early stationary phase, when serial dilutions were also plated. Incubations were carried out at 37°C under aerobic or anaerobic conditions and then colony forming units (cfu) per mL were counted. These experiments were performed in triplicate.

WH1(A31V/ΔN37)-mCh expression was induced under aerobiosis as indicated above. For RNA purification, the RNeasy kit (Qiagen) was used, followed by in-column DNaseI digestion (RNase-free, Roche; 10 μL, 2 h at 37°C). The purity of the RNA preparation was assessed first through AGE (0.8% agarose in TAE buffer, samples pre-incubated in 50% formamide buffer, at 95°C for 2 min) and then in a Bioanalyzer 2100 RNA chip (Agilent). Final RNA concentrations ranged between 0.5 and 0.75 μg⋅mL^-1 and their absorption ratios at 260/280 nm were between 2.13 and 2.45. Equal amounts of each RNA sample were retro-transcribed to DNA using random sequence oligonucleotide hexamers as primers. Template RNAs were then degraded with NaOH and cDNAs were labeled using TdT DNA polymerase and ddUTP-biotin. Labeled cDNAs were hybridized on GeneChip^® E. coli Genome 2.0 arrays (Affymetrix), which span 10,000 probesets from the pangenome of four E. coli strains (including MG1655, the parental for MDS42) and casted on a Fluidics Station 450 (Affymetrix) at 45°C for 16 h. Arrays were washed, stained with phycoerythrin-conjugated streptavidin and then fluorescence emission at 570 nm was digitized in a GeneChip^® Scanner 3000 7G (Affymetrix), as specified by the supplier. Microarrays were identically processed for three independent biological replicas. Data were normalized with the RMA algorithm (Affymetrix Expression Console software) and analyzed using the Babelomics software package (Medina et al., 2010). Statistical analysis of the results was performed through the limma t-test with Benjamini–Hochberg’s FDR correction: genes with false discovery rates (FDR) ≤ 0.05 were classified as significantly induced/repressed. Data were manually filtered to discard low score (background) genes not present in the MDS42 genome (Pósfai et al., 2006). Genes with A31V/ΔN37 expression ratios either higher than 2 or lower than 0.5 were selected as the fraction of the E. coli genome preferentially expressed or repressed, respectively, in response to WH1(A31V)-mCh amyloidosis. Microarray data are available at the Gene Expression Omnibus database (GEO) under the accession number GSE69517.

After induction of MDS42 cells carrying either WH1(A31V)-mCh or WH1(ΔN37)-mCh (see above), 13 A_{600 nm} units were processed at 0.5, 1, and 2.5 h by lysing the cell pellets with 1.5 mL of 20 mM Hepes⋅NaOH pH 6.0, 0.1 M NaCl, 0.5% sulfobetaine 12 (SB-12), 0.5% Na-deoxycholate, 1 mM EDTA, 50 μg.mL^-1 RNaseA, plus a protease inhibitors pill (Roche). Cell lysates were then centrifuged at 12,000 rpm for 1 h at 4°C. Pellets were resuspended in 1.5 mL of the same buffer, but with 1.0 M NaCl and no RNaseA, and they were sonicated (Branson ultrasonic homogenizer, thin tip) for 30 s and centrifuged as above. The sedimented fraction was resuspended in 250 μL of 20 mM Hepes⋅NaOH pH 6.0, 0.1 M NaCl, 1 mM EDTA and this suspension was then carefully layered on a discontinuous sucrose (20–40% in the same buffer) cushion and centrifuged overnight at 12,000 rpm and 4°C. Pellets were subsequently resuspended in Laemmli buffer (x2), their component proteins analyzed by SDS-PAGE (10% polyacrylamide) and then gels stained with Coomassie blue. Proteins bands over and below WH1(A31V/ΔN37)-mCh were excised, cut into pieces and digested in gel (50 mM NH₄HCO₃, overnight at 30°C) with bovine trypsin (12.5 μg⋅mL^-1). Peptides were extracted in acetonitrile and 0.5% trifluoroacetic acid, cleaned through a ZipTip (C18 matrix; Millipore) and resuspended in 0.1% formic acid, 2% acetonitrile (buffer-A). Peptides were processed as described (Barderas et al., 2013). Briefly, peptides were trapped in a C18-A1 ASY-Column (Thermo Scientific) and, upon elution, loaded into a Biosphere C18 column (NanoSeparations). A 125-min gradient (250 nL⋅min^-1) from 0 to 35% buffer-B (0.1% formic acid in 100% acetonitrile), followed by steps to 45% (15 min) and 95% (10 min), was developed in a NanoEasy HPLC coupled to a nanoelectrospray ion source (Proxeon). Mass spectra (m/z 300–1700) were generated in an LTQ-Orbitrap Velos MS (Thermo Scientific) in the positive ion mode and acquired with a target value of 1,000,000 at a resolution of 30,000 (m/z 400). The 15 most intense ions were selected for collision-induced fragmentation in the linear ion trap with a target value of 10,000 and normalized collision energy of 38%. Raw MS files were searched with the SEQUEST algorithm (Eng et al., 1994) against the E. coli MDS42 proteome (UniProt). Peptides were validated with Percolator (Spivak et al., 2009), scoring as positive those proteins with ≥3 identified peptides per target, or with a peptide spectrum match (PSM) value ≥ number of identified peptides and XCorr > 3. Proteins represented in the mass spectra by a single peptide were not considered, except when PSM > 3. If present in both datasets, proteins classified as co-aggregated with ΔN37 were then subtracted from those listed for A31V. The whole procedure was repeated for three independent biological replicas. Proteins found at least twice as preferentially co-aggregated with the A31V variant were selected as the fraction of the E. coli proteome co-aggregated with WH1(A31V)-mCh.

The lists of genes preferentially induced/repressed or co-aggregated with WH1(A31V)-mCh, but not with the ΔN37 variant, were processed in parallel in a similar way, including Boolean algebra analysis with Venny¹, classifying genes (or proteins) as early when present just in the 0.5 h dataset or when found both at 0.5 and 1.0 h, middle when exclusively placed in the 1.0 h dataset, and late when present at 2.5 h alone or both at 1.0 and 2.5 h. Gene ontology (GO) functional classification was performed with the EcoCyc database (Keseler et al., 2013). The curated transcriptomic and interactomic datasets were finally crossed using the STRING 10.0 tool (Szklarczyk et al., 2015) to get a comprehensive set of the functional pathways and protein clusters involved in WH1(A31V)-mCh amyloidosis.

Bacterial cultures were grown as indicated above. One mL aliquots were collected at post-induction intervals, cells removed by centrifugation at 13,000 rpm for 5 min, and the culture supernatants were processed through 0.2 μm filters and stored at -80°C. Samples were analyzed in triplicate, as described in Felpeto-Santero et al. (2015). Twenty microliter samples were injected into an Aminex HPX-87H column (Bio-Rad) coupled to a Gilson HPLC system. Elution was performed at 0.6 mL⋅min^-1 in 5 mM H₂SO₄. Identification and quantitation of the acetate and succinate peaks were carried out using 32 Karat (v. 8.0; Beckman-Coulter). Metabolite concentrations were extrapolated from the elution profiles of calibrated solutions of acetate and succinate. Plots were corrected according to the dry weight of bacterial pellets.

Bacterial cultures were grown to OD_{600 nm} = 0.4 and 400 μL plated on LB agar with 100 μg⋅mL^-1 ampicillin and 0.5 mM IPTG. When indicated, plates were supplemented with ascorbic acid to 1.5 mM to neutralize hydrogen peroxide. Sterile filter paper disks (Whatman, 0.5 mm ∅) were embedded with 0.001% H₂O₂ or 0.0025% (w/v) paraquat (Sigma), and then laid on the plates and cultured at 37°C overnight. For the Δndh SLC22 cells (Woodmansee and Imlay, 2002) H₂O₂ was tested up to 0.5%. Areas of the inhibition halos were estimated on photographs, subtracting the area of the paper disks.

The hyper-amyloidogenic A31V variant of RepA-WH1 (Giraldo, 2007) becomes metastable and highly cytotoxic upon fusion to the monomeric red fluorescent protein mCherry (Gasset-Rosa et al., 2014). The resulting prion-like protein, WH1(A31V)-mCh, has the ability to assemble pores in model lipid vesicles that mimic the E. coli inner membrane, thus leaking their contents while not suffering lysis (Fernández et al., 2016b). Expression of WH1(A31V)-mCh in the E. coli K-12 MDS42 strain resulted, when bacteria were observed at the microscope (Figure 1A), in a significant proportion of ‘ghost’ cells. In a clear indication for a weakened integrity of the membrane, cells lost their normal turgor but, as for the vesicles, did not lyse retaining their large size components such as the nucleoid and the prionoid aggregates. On the contrary, bacteria expressing the soluble mCherry reporter did not show any difference in morphology compared with the parental strain.

The integrity of the cell membrane is critical to the generation of a PMF, which drives ATP synthesis by the membrane-bound ATP synthase. If, as observed in vitro (Fernández et al., 2016b), WH1(A31V)-mCh targets the inner membrane through pore formation, membrane integrity is expected to be compromised, with the subsequent reduction of PMF-dependent processes such as ATP synthesis. To test this hypothesis, we measured the concentration of ATP in cell lysates from bulk E. coli cultures grown aerobically in rich medium, by measuring the in vitro activity of the ATP-dependent firefly luciferase: a progressive reduction in luminiscence (up to ≈ 70% at ≥ 2.5 h) was observed upon the expression of the prionoid (Figure 1B, left). In a different bioluminiscence assay, based on the constitutive in vivo expression of the bacterial luxCDABE operon, ATP was consumed by LuxD in the synthesis of the substrate for the LuxAB luciferase. In this case, the expression of WH1(A31V)-mCh also led to a net reduction (by ≈ 75%) in luminiscence emission (Figure 1B, right). Both results point to a significant drop in the intracellular amount of ATP and thus are consistent with a scenario of compromised bioenergetics.

We then focused on iron uptake to probe the integrity of the inner cell membrane further. Iron is an essential co-factor in many reactions central to aerobic metabolism, especially those involving the oxidoreduction of substrates. Being a scarce resource, Gram-negative bacteria have evolved siderophores, scavenger molecules with high-affinity and specificity for iron (Frawley and Fang, 2014). Once synthesized, siderophores are secreted through both membranes and, after extracellular coordination of the Fe³⁺ ion, they are internalized in a process that is dependent on both PMF and ATP consumption. Upon reduction to Fe²⁺, the metal is released in the cytoplasm to be assembled as mononuclear iron or as (Fe-S) clusters in metalloproteins. So, the intracellular level of iron provides another estimation of the ability of the cell membrane to support transport and thus on its integrity. We determined the intracellular concentration of iron across the time course of the induction of WH1(A31V)-mCh (Figure 1C). Ferrous iron increased steadily for 2.5 h in both the naïve and prionoid-expressing cells but was significantly lower (about 50% after 1 h) in the cells undergoing amyloidogenesis.

The findings reported in this section are consistent with a reduction in PMF, and thus in ATP synthesis, due to prionoid-elicited leakage through the inner membrane.

Targeting of the inner bacterial membrane by amyloids is a mechanism of cytotoxicity that must be operating whatever is the final acceptor in the electron transport chain. E. coli is a facultative anaerobe. Therefore, it made sense to survey whether prionoid cytotoxicity occurred under aerobic and/or anaerobic growth conditions. This study was carried out in parallel upon the expression of two distinct mutant variants of RepA-WH1, A31V and ΔN37, both fused to mCherry: while the former is hyper-amyloidogenic and highly cytotoxic (Giraldo, 2007; Gasset-Rosa et al., 2014), the latter, lacking the amyloidogenic stretch in RepA-WH1, aggregates as conventional IBs and has a milder cytotoxicity (Gasset-Rosa et al., 2014). Relative to the maximum optical density reached by the cells freed of the prionoid, under aerobic conditions a 60% reduction was observed for the cultures expressing the prionoid (Figure 2A, left), whereas in anaerobic growth such reduction was just 20% (Figure 2A, right). The viability of cells was then checked at three points of the respective growth curves: pre-induction, middle exponential and early stationary phases. As expected from the cell densities achieved (Figure 2A), the number of colonies per mL of culture, once plated on agar, was an order of magnitude higher for bacteria grown under aerobiosis than for those in anaerobiosis (Figure 2B). The most noticeable difference was that, under both physiological conditions, the expression of WH1(A31V)-mCh drastically reduced (to 10–20%) the viability of the bacterial population, whereas WH1(ΔN37)-mCh did not in a significant way. These results indicated that the expression of WH1(A31V)-mCh indeed is cytotoxic. However, the ΔN37 mutant has no deleterious effect and thus the reduction in growth observed for this variant (Figure 2A) must be a burden on fitness imposed by the formation of IBs. As E. coli is usually grown under aerobic conditions, and these actually are closer to the environment for human cells undergoing amyloidoses, the rest of the experiments reported here were carried out in aerobiosis.

Transcriptomic analysis provided clues on how bacteria react to the expression of the prionoid downstream of its primary target, the inner cell membrane. In a subtractive gene expression approach using microarrays, WH1(ΔN37)-mCh IBs were used as a reference set for WH1(A31V)-mCh, thus suppressing from the output list genes involved in the unspecific cellular response to protein aggregation/IBs, such as molecular chaperones and quality control proteases (Winkler et al., 2010). This focused the study on features specific for the acute cytotoxicity of the prionoid. The same E. coli strain used above, MDS42 (Pósfai et al., 2006) was selected again as host bacteria because its reduced genome, devoid of non-essential genes, simplified the transcriptomic analysis. In previous studies (Fernández-Tresguerres et al., 2010; Gasset-Rosa et al., 2014), time-lapsed fluorescence microscopy allowed us to characterize 30 min as the post-induction time interval in which WH1(A31V)-mCh aggregates started to become evident in a substantial fraction of the cells, and 2.5 h as the point where cytotoxicity was notorious in the form of stalled cell division, increased filamentation and subsequent cell death, which became dominant at ≥4 h. We therefore carried out the analysis at 0.5 and 2.5 h, plus an intermediate sampling point (1 h).

Cells from bacterial cultures expressing either WH1(A31V)-mCh or WH1(ΔN37)-mCh were harvested at the three indicated post-induction times. Total RNA samples were hybridized with DNA microarrays that probed the complete transcriptome of E. coli. Differentially expressed genes from the comparison of the A31V and ΔN37 datasets were classified as induced (≥2-fold expression level in A31V vs. ΔN37, i.e., A31V/ΔN37 ratio ≥ 2.0; in red in Figure 3A) or repressed (≥2-fold expression level in ΔN37 vs. A31V, i.e., A31V/ΔN37 ratio ≤ 0.5; in green in Figure 3A) (Supplementary Dataset S1). Genes were then grouped (Figure 3B) as early expressed (130 genes), if the levels of their mRNAs were altered only at 0.5 h, or both at 0.5 and 1.0 h; middle (98 genes), if they appeared in the list exclusively at 1 h; and late (145 genes), if they were altered after both 1.0 and 2.5 h, or just at 2.5 h. These three classes comprised most of the genes, with just a few being excluded due to their ubiquitous presence or to their simultaneous clustering at the initial and final datasets. Overall, the E. coli transcriptome indicated an initially repressive response to the expression of WH1(A31V)-mCh (86.9% genes differentially repressed vs. 11.5% induced, compared to ΔN37, in the early group class), with a progressive reactivation of the gene expression program (73.5% genes repressed vs. 26.5% induced; middle), which finally became dominant (28.3% genes repressed vs. 69.7% induced; late).

Functional annotation of the genes differentially affected by WH1(A31V)-mCh expression revealed (Figure 3C) a major fraction encoding membrane-located proteins, closely followed by metalloproteins, especially at shorter times. Other functional groups included stress response genes and DNA/RNA-binding proteins, such as transcriptional regulators, which became significant in the late class accounting for the observed reactivation of gene expression. Early repressed genes included many dehydrogenases, terminal reductases and enzymes of the anaerobic metabolism having in common iron as cofactor. This was also the case for the catalase katG, a major detoxifier of H₂O₂ (Imlay, 2008, 2013) and the most repressed gene in the whole transcriptomic dataset (Supplementary Dataset S1). Among the few differentially overexpressed early genes, were notable those for the synthesis and transport of siderophores (iron uptake pathway), such as cirA, efeO, entC, fhlA and fhuF (Frawley and Fang, 2014). This response was in agreement with the observed reduction in the levels of intracellular iron (Figure 1C). The inductions of the H₂O₂-responsive gene ychH (Lee et al., 2009) and ndh were also significant. The latter encodes NdhII, the major NADH-dehydrogenase in exponentially growing E. coli cells (Messner and Imlay, 1999), which is typically induced in response to limiting concentrations of intracellular iron (Folsom et al., 2014). On the contrary, other dehydrogenases effective in generating a PMF (Unden and Bongaerts, 1997) were repressed. The highest early expression was achieved for fnr, which encodes the oxygen-labile Fe-dependent transcription factor regulating the switch between aerobic and anaerobic metabolism (Myers et al., 2013). The middle group class also showed the increased expression of iron uptake genes (efeBU, entES, fepABCG, fes, fhuE, fiu) and of RyhB, an antisense RNA that is the main repressor of genes encoding iron-metalloenzymes (Massé et al., 2005), whereas the gene encoding ferritin (ftnA), a major Fe-storage protein, was repressed. In addition, the expression of genes responsible for the response against oxidative stress was enhanced through the regulatory antisense RNA OxyS. Expression of genes for (deoxy)ribonucleotide triphosphate synthesis, such as ndk and nrdH, and importers of anti-oxidant polyamines like potG, was enhanced at the transition to the late group class, when cell viability was already severely compromised. Other functional late processes included the assembly of (Fe-S) clusters (hscAB, iscX, sufA; being the latter the second highest expressed gene), the responses to osmotic (putA) and acidic (hdeB) stresses, and elements of the genome maintenance (deoA, holB, recR, rarA) and cell division (ftsBI, mrdB, murG) machineries. Relevant to the latter response, it has been recently found that filamented E. coli cells with compromised membrane integrity overexpress cell division genes (Sánchez-Gorostiaga et al., 2016).

The loss of function caused by the assembly of proteins into amyloids is usually associated with co-aggregation of a subset of the cell proteome leading, if not to cytotoxicity itself, to the aggravation of the proteinopathic condition (Olzscha et al., 2011; Hosp et al., 2015). To explore whether the amyloidogenesis of RepA-WH1 led to the differential co-aggregation of particular proteins from the E. coli proteome, we undertook the purification and characterization (Figure 4) of the aggregated protein subset from bacteria expressing either WH1(A31V)-mCh or its milder version WH1(ΔN37)-mCh, at the same time intervals previously surveyed through genomic approaches (Figure 3). Protein aggregates from three independent cultures were first purified by centrifugation through discontinuous gradients of sucrose, and subsequent separation of the sediment by means of SDS-PAGE (Figure 4A). Gel tracks were split into slices and then proteins were digested in situ with trypsin. The resulting peptides were extracted and analyzed by nano-scale HPLC combined with mass spectrometry (ESI-MS). Peptides were identified in sequence databases and then classified (Figure 4B) following the same criteria used for the microarray studies (Figure 3B).

Proteins identified as preferentially co-aggregating with the WH1(A31V)-mCh prionoid, but not with the WH1(ΔN37)-mCh IBs, (Figure 4C and Supplementary Dataset S2) were less than those inferred from the transcriptomic studies (Figure 3): 24 proteins were consistently found (i.e., they were present with a significant score in at least two out of three biological replicas) at the early time interval of expression, 45 at the middle class and 59 at the late group (Figure 4C). Overall, functional annotation revealed that membrane proteins were underrepresented in the datasets, as expected for cytoplasmic aggregates, whereas proteins involved in the response to different types of stress were overrepresented, albeit decreasing along the time course, with the gene expression and transition metal binding functional classes ranking second and third, respectively (Figure 4D). The master regulator of the general stress response RpoS (σ³⁸/σ^S) (Battesti et al., 2011) was among the factors aggregating at the early time interval. In the middle group, the RpoS inhibitor RssB was found together with a number of proteins involved in the response to oxidative stress such as its master regulator OxyR (Aslund et al., 1999; Seo et al., 2015), the alternative catalase KatE, and the glutathione reductase Gor (Imlay, 2008, 2013). The (Fe-S) cluster scaffolding proteins IscU and NfuA (Jang and Imlay, 2010) were also placed in this subset. In the late class, BetA, an enzyme for the synthesis of the osmo-protectant betaine (Lamark et al., 1996) and DNA repair enzymes such as RdgC and XthA were identified. It is noteworthy that several enzymes in the glycolytic (pyruvate kinase II, PykA; triosephosphate isomerase, TpiA), TCA (malate dehydrogenase, Mdh) and mixed acid fermentation (acetate kinase, AckA) pathways appeared aggregated with RepA-WH1(A31V)-mCherry at the early and middle subsets.

The lists of genes up/down regulated in the transcriptomic analysis (Figure 3) and of proteins found as preferentially co-aggregated with WH1(A31V)-mCh (Figure 4) were then compared. The assumption was that differential gene expression and protein sequestration might be independent contributors to RepA-WH1 amyloidosis and thus complementary, rather than overlapping, views to the core cellular processes involved in the ‘disease.’ Indeed only eight proteins, and their respective genes, were present in both ‘omic’ datasets (1.6% of a total of 501).

Network analysis of the combined set of genes or proteins allowed their assignment to over 40 functional clusters (Figure 5), which could be broadly grouped into eight core functions: hydrocarbon metabolism, respiration [i.e., electron transport, NAD(P)H oxidoreductases and hydrogenases]; nucleotide/phosphate and nucleic acids metabolism; transport through membranes; cell division; iron uptake; (Fe-S) clusters biogenesis; and response to various stresses (with a focus on detoxification of hydrogen peroxide). In terms of the regulatory response(s) to the aggregation of WH1(A31V)-mCh, the analysis of the combined transcriptomic and interactomic datasets revealed that the master regulators of the transcriptional switches in response to oxygen levels, Fnr (Myers et al., 2013), and to general stress, RpoS (Battesti et al., 2011), were directly controlling the expression of substantial fractions (16.21 and 6.64%, respectively, with 1.95% regulated by both) of the genes linked to RepA-WH1 amyloidosis (Figure 6). Other transcription factors, such as OxyR, ArcA, Fur, RpoN/E, PhoB, LexA or CpxR, fell well behind.

The assays presented above converge in a picture of damage to the bacterial inner membrane by WH1(A31V)-mCh with the subsequent reduction in PMF-dependent transport of metabolites and co-factors, such as iron. Limiting iron levels would promote the expression of the NdhII dehydrogenase that, under aerobic conditions, would generate ROS, while a battery of the proteins responsive to oxidative stress would become disabled by co-aggregation with the prionoid. With the aim of validating this sketch of the bacterial amyloidosis, we undertook additional functional assays in E. coli cultures expressing WH1(A31V)-mCh or WH1(ΔN37)-mCh under the same conditions surveyed through the genomic and interactomic approaches.

Replenishment of ATP from ADP has other sources apart from ATP synthase: the reactions of the central carbon metabolism and substrate-level phosphorylation. Upon the impairment of ATP synthase activity due to the disruption of PMF by membrane leakage, cells would become dependent on less efficient metabolic fluxes (see above; Figure 1B). Thus, glycolysis must be enhanced, as suggested by the observed induction of the pyruvate kinase gene (pykF) in cells expressing WH1(A31V)-mCh (Figure 3A). However, this does not seem to be the case probably due to the co-aggregation with the prionoid of triosephosphate isomerase (TpiA; Figure 4C). Therefore, other alternative sources for ATP regeneration were explored.

Determination by HPLC of the extracellular levels of succinate, a key intermediate in the TCA cycle, showed that expression of the prionoid resulted in a net 30% decrease in this metabolite after 1 h (Figure 7A). This probably reflects an early blockage in the TCA cycle due to the co-aggregation of malate dehydrogenase (Mdh) with WH1(A31V)-mCh (Figure 4C), besides the impossibility to regenerate NAD⁺ at the level of the electron transport chain. Interestingly, succinate levels remained more elevated for the ΔN37 than for the A31V variant of RepA-WH1, resembling the behavior of wild-type cells.

In rapidly growing E. coli cells, potentially leading to oxygen-limiting conditions, extra reducing power and ATP are usually generated through mixed-acid fermentation, whose products (acetate in particular) are secreted to the medium but, upon reaching stationary phase, are imported to be further metabolized (Förster and Gescher, 2014). Such double-way metabolic flux was observed in the HPLC determination of the levels of acetate in the culture medium of bacteria not expressing the prionoid (Figure 7B). However, upon the expression of WH1(A31V)-mCh a significant decrease (up to 30%) in the levels of acetate was detected at 2.0–2.5 h post-induction, suggesting a reduction in the production of ATP at substrate-level phosphorylation. This fact could be due to the co-aggregation of acetate kinase (AckA) in the early interactomic dataset (Figure 4C), but also to an impaired flux through glycolysis and fermentation (see above). On the contrary, the acetate profile for cells expressing WH1(ΔN37)-mCh was closer to that found in control cells. We attempted to measure the levels of other metabolites, but the results were inconclusive due to the high variability between replicas.

Overall, these results are consistent with a primary disruption in PMF by the RepA-WH1 prionoid, reinforced by a net reduction in the fluxes through both central carbon metabolism and mixed acid fermentation.

Our transcriptomic analysis on E. coli cells in aerobiosis had shown that katG, the gene coding the major catalase/peroxidase at the exponential growth phase (Imlay, 2008, 2013), was the most repressed at the early time interval upon WH1(A31V)-mCh expression (Figure 3A and Supplementary Dataset S1). In addition, interactomics had identified the alternative stationary phase catalase KatE as significantly trapped in the intracellular aggregates of the prionoid (Figure 4C and Supplementary Dataset S2) (Imlay, 2008, 2013). These observations meant that E. coli cells suffering from WH1(A31V)-mCh amyloidosis must exhibit increased sensitivity toward stress by hydrogen peroxide. On the contrary, no superoxide dismutase (SodABC) showed altered expression, or differential co-aggregation, upon expression of the A31V or ΔN37 variants. Therefore, bacterial cells undergoing the WH1(A31V)-mCh amyloidosis must not be differentially sensitive to superoxide.

We thus challenged bacteria with diluted H₂O₂ (Figure 8A, left) or paraquat (Figure 8A, middle), a generator of superoxide radicals (O2•−), and tested their effects in a zonal growth inhibition assay on agar plates. Briefly, lawns of cells expressing the control marker mCherry, or its fusion to WH1(A31V) or WH1(ΔN37), were seeded just before laying filters pre-embedded with the oxidizing agents. Quantitation of the areas of the inhibition halos revealed (Figure 8A, right) that the expression of WH1(A31V)-mCh correlated with a net hindrance of bacterial proliferation by H₂O₂ (125% increase in area, compared with the mCherry control), an inhibition higher than that observed upon expression of the ΔN37 variant (43% increase). However, no significant differences were appreciated when the three bacterial strains were treated with paraquat. As expected, the inhibitory effect of H₂O₂ was relieved by the inclusion of a reducing agent (ascorbate) in the medium (Figure 8A, left).

These results support an impairment, dependent on WH1(A31V)-mCh, of the cellular response against the oxidative stress caused by H₂O₂.

Growth of bacteria under aerobic conditions generates vast amounts of ROS (up to μM intracellular concentrations) (Messner and Imlay, 1999). In cells undergoing WH1(A31V)-mCh amyloidosis, the only differentially induced NADH-dehydrogenase at the early stage was NdhII (encoded by ndh; Figure 3A). NdhII is expressed in response to limiting levels of iron (Folsom et al., 2014) and generates ROS through the auto-oxidation of its FAD cofactor (Messner and Imlay, 1999; Woodmansee and Imlay, 2002; but see Seaver and Imlay, 2004). So, an increase in oxidative stress was expected as a side effect of the observed rise in the intracellular levels of NdhII, with the possible consequence of a higher sensitization of cells to exogenous oxidizing agents. To test this hypothesis, zonal growth inhibition assays with H₂O₂ were performed in a Δndh (null) mutant E. coli background (Woodmansee and Imlay, 2002). The results (Figure 8B, left) revealed a net reduction in the sensitivity of the mutant bacteria to the additional stress imposed by exogenous hydrogen peroxide: up to a 500-fold increase in H₂O₂ concentration was required to get inhibition halos with an area close to that observed in the ndh⁺ background, while keeping the trend of the higher sensitivity of bacteria expressing WH1(A31V)-mCh (Figure 8B, right).

These results suggest that induction of the alternative dehydrogenase NdhII is a relevant source of ROS in bacteria undergoing WH1(A31V)-mCh amyloidosis, to the point of overtaking proteins involved in detoxifying H₂O₂, a defense line already feeble due to their co-aggregation with the prionoid (Figure 4C).